Early-stage research on caloric refrigeration

The vapor-compression method that is commonly used for refrigeration and space cooling today involves the use of gaseous refrigerants that are harmful to the environment. An alternative, environmentally benign and energy-efficient method called caloric refrigeration is based on solid refrigerants that change their temperature upon introduction of external fields such as magnetic, stress, or electric. The focus of the project will be on the early-stage research of magneto and elastocaloric devices, which will include both experimentation and modeling.

Mentor: Agata Malgorzata Czernuszewicz

Research Area: Engineering Mechanical

Unraveling the Nature of Bonding in Unusual Molecules

There are a great many different ways that molecules "stick together" to form what is called a bond. We are mostly familiar with bonds in organic molecules, like C-C or C=O bonds. How do these bonds form? What holds them together? What about more unusual molecules, like C-Xe bonds that have been found in space? Do these bonds have the same origin as those in "simple" organic molecules or are they different? How about bonds in molecules that contain heavy elements that require the incorporation of relativistic effects? We have developed a general method for understanding and interpreting the nature of chemical bonding in the broad array of chemical environments. The participating SULI student will use this method in our quantum chemistry program GAMESS to study interesting and unusual molecules.

Mentor: Mark Gordon

Research Area: Theoretical Chemistry

Bioinspired Metamaterials

This collaborative project focuses on developing fundamental knowledge leading to bioinspired approaches and novel fabrication techniques for creating nanoscale structures that, when assembled in 2D and 3D, serve as functional metamaterials with interesting optical properties (such as negative refractive index cloaking materials). The two main goals of the project are to 1) develop the underlying science to design, synthesize and characterize individual metallic nanostructures, and 2) devise approaches to assemble these individual nanostructures into 2D and 3D mesoscale superstructures. This collaborative project funded by DOE employs an integrated approach for synthesis (using DNA as well as synthetic polymer templates), and characterization, guided by theory and computation.

Mentor: Surya Mallapragada

Research Area: Nanotechnology

Controlled isotope labelling of silica surfaces for catalysis studies

Molecular catalysts are grafted to solid oxide supports, such as silica, to be immobilized and form more stable, and easily separable, heterogeneous catalysts. The grafting reactions are generally thought to proceed through a protonolysis mechanism, wherein a metal site replaces the hydrogen atom from a surface hydroxyl, although some have postulated that metal catalysts may also react with the more inert siloxane linkages. Whether this secondary reaction occurs has important implications on our goals to design well-defined single-site heterogeneous catalysts.

The best approach to determine whether these reactions would occur would be using 17O solid-state NMR spectroscopy. Generally, we can distinguish the 17O NMR signal from a metal-bound oxygen (Si-O-M) from those of silanols (Si-O-H) and siloxanes (Si-O-Si). In theory, to determine whether silanols are the only sites that participate in grafting reactions we would want to make two silica materials, one with only the silanols labelled in 17O, and one where only the siloxanes are labelled. Unfortunately, current approaches to 17O-enrichment of silica are non-selective, enriching both the silanols and the siloxanes. More specifically, this approach involves high temperature dehydration-rehydration of silica. We will investigate whether silanols can be preferentially exchanged when using mild conditions by studying the isotope exchange using in situ 17O NMR spectroscopy. We will vary the pH of the enriched water and monitor how this affects the exchange rate for siloxanes and silanols.

Assuming we find a reliable approach to selectively-enrich specific sites on the silica surface, we will then graft organometallic species to the supports and acquire 17O solid-state NMR spectra to determine whether a Si-O-Zr moiety was formed. Catalytic conditions will be simulated by bringing the material to an elevated temperature and monitoring how the 17O NMR spectrum changes. Changes in metal-surface bonding would particularly be interesting and provide a clear target for improving the inertness of catalyst supports.

Mentor: Frederic Alain Perras

Research Area: Physical Chemistry

Molecular Modeling of Deep Eutectic Solvents to study solvent effect

Deep eutectic solvents (DESs) have become popular as a promising candidate for diverse applications, e.g., extraction of natural compounds, catalysis, and carbon dioxide capture. They are also considered as green solvents since each DES component is inexpensive and environmentally benign. However, the understanding of DES remains elusive. In this project, we aim to extract key interactions between each component of DES by using quantum chemical-based calculations. The outcome of this study will provide a better understanding of solute-solvent interactions and aid in the development of high-throughput separation technologies.

We believe that students from a variety of backgrounds, ranging from math, computer science to physics, chemistry or biology can all benefit from the project. During the project, the student will learn a range of techniques from utilizing molecular modeling to analyzing intermolecular interactions of novel solvents.

Mentor: Tosaporn Sattasathuchana

Research Area: Theoretical Chemistry

Computational Studies on Assembling Nanoparticles

Materials built from nanocrystals (NCs) as their foundational units, rather than atoms or molecules, stand out as key contenders in tackling contemporary technological challenges. This project entails students in predicting the assembly processes of nanomaterials and assessing the overall stability of these assemblies, with a focus on exploring potential functional properties. Our research group has devised diverse computational methods to predict the rational design of NC materials such as programmable self-assembly through DNA, electrostatic phase separation of neutral polymers, attachment of irreversible dithiol linkers, interpolymer complexation, Nanocomposite Tectons, and solvent evaporation. Students will initially acquaint themselves with the group's Python-operated software packages and subsequently use them for structural predictions, placing particular emphasis on calculating free energies and comparing the stability of different structures. The specific systems under investigation feature nanoparticles functionalized with polyethylene oxide polymers, and collaborative efforts with the ongoing FWP on biomineralization are integral to this activity.

Mentor: Alex Travesset

Research Area: Nanoscience

Assembly of Nanoparticles in Water: Computational Studies

Nanocrystals, rather than atoms or molecules, form the fundamental units of materials that show great promise in addressing key technological challenges of our era. This project engages students in predicting novel properties of nanomaterials and determining the optimal experimental conditions for their successful assembly. Our research group has developed various computational methods for understanding and foreseeing the rational design of nanocrystal materials in programmable self-assembly through DNA, electrostatic phase separation of neutral polymers, attachment of irreversible dithiol linkers, interpolymer complexation, Nanocomposite Tectons, and solvent evaporation. Initially, students will acquaint themselves with the group's software and then apply it to make structural predictions. The specific systems under investigation feature nanoparticles grafted with polyethylene oxide polymers, and collaborative efforts with the ongoing FWP on biomineralization are integral to this endeavor.

Mentor: Alex Travesset

Research Area: Nanoscience

Complex Magnetic Structures and their Excitations

We use quantum and classical models to determine magnetic structures and the interactions that lead to these structures through the analysis of elastic and inelastic neutron scattering results. We are exploring magnetic structures in forefront quantum materials that exhibit topological electronic properties (i.e. topological insulators and flat-band materials). We synthesize these materials and conduct neutron diffraction and inelastic scattering, and from the analysis of the results, we obtain the magnetic ground states of these systems. We also analyze the magnetic excitations, and by modeling them through efficient optimization methods, we determine the interactions that set up the magnetic structures. The information we get is important in developing electronic devices that take advantage of the electronic and magnetic properties of these materials (i.e., the area of spintronics).

Mentor: David Vaknin

Research Area: Quantum Materials

Assembling and Crystallizing Nanoparticles

We use X-ray diffraction techniques to determine the structures of assembled nanoparticles (NPs) either at the liquid/vapor interface or in bulk. In order to assemble NPs, we modify their surfaces by grafting them with various polymers (water or solvent-soluble). We then modify the conditions of the solvent (pH, salinity, temperature, etc.) to explore conditions under which the NPs aggregate in an ordered structure. We use various synchrotron X-ray diffraction and spectroscopic techniques to determine the structures and the viable parameters that lead to high-quality crystallization. The student will conduct X-ray scattering with the group (if the allocation of beamtime at the synchrotron coincides with the SULI program) and will be involved in the structural analysis of X-ray results using Python routines and Jupyter notebooks.

Mentor: David Vaknin

Research Area: Nanoscience

Carbon capture with nitrogen-doped carbon materials

Mesoporous nitrogen assembly carbons (NACs) are developed as a promising solid carbon capture material with high surface area and tunable selectivity. The high electrical conductivity of carbon materials also allows their usage as both adsorbent and electrocatalysts. Ames Laboratory has established expertise now in synthesizing NACs with well-defined porosity. However, due to their partially amorphous structure, understanding the structures of such carbon materials and subsequent optimization of the material is challenging experimentally.

The goal of this project is to advance the development of carbon capture materials by using the first-principle simulations. In this project, we will investigate the key structural motifs in the NAC as it is challenging to elucidate the structures of these materials experimentally. We will also study the chemical and intermolecular interactions between the sorbent and sorbate, which will uncover the role of different structural motifs plays for the selectivity of NACs.

We believe that students from a variety of backgrounds, ranging from math, computer science to physics, chemistry or biology can all benefit from the project. During the project, the student will use the computational chemistry packages, GAMESS, and acquire basic understanding on quantum mechanics and the theory of intermolecular interactions, as well as running and analyzing molecular simulations.

Mentor: Peng Xu

Research Area: Materials Sciences

Weak but important: intermolecular interactions

Weak, non-covalent interaction between molecules (intermolecular forces) are ubiquitous and important across chemistry, biochemistry and material science fields. However, accurately modeling these interactions is very challenging. We have developed a computationally affordable ab initio force field method that balance computational efficiency and accuracy. This method has been applied to many interesting systems, including water, common organic solvents (ethanol, methanol, benzene) and biological systems (peptides and DNA).

This project will focus on improving the performance of this ab initio force field method at relatively short range: the molecules are not forming covalent bond yet, but the overlap between the molecular orbitals from the interacting molecules can be substantial. The improvement made in this project will significantly improve the quality of the outcomes predicted by molecular dynamics or Monte Carlo simulations using this method.

The codes that run the calculations are written in Fortran, and the workflow scripts (set up inputs, submit inputs and analyze outputs, etc.) is written in Python. Fortran or Python programming knowledge is desired but not required. A basic understanding of Unix/Linux commands and text editor (such as vim or emacs) would be helpful.

Mentor: Peng Xu

Research Area: Theoretical Chemistry

Unifying the codes for adaptive variational quantum algorithms

Multiple near-term quantum algorithms have been developed to simulate ground state, dynamics and finite-temperature properties of electron and spin models. These algorithms are based on variational principles, with parametrized circuits adaptively constructed to guarantee the high fidelity. Individual implementations of the algorithms with further technical advances are available; however, they are loosely bounded although they share a common algorithmic structure. Here we propose the development of a unified computational package for this set of adaptive variational quantum algorithms for better efficiency, extendibility and accessibility for the community. The project will be supervised by the principle investigator who is the leading author of the multiple codes already developed. At the end of the project, a paper submitted to the Journal of Open Source Software is expected.

Mentor: Yongxin Yao

Research Area: Quantum Computing

Building New solid ruthenium pincer catalysts for ester reduction

Organic esters are common functional groups but are challenging to reduce. Reduction of esters
typically requires highly reactive reagents, such as lithium aluminum hydride, in stoichiometric
quantities that generate large quantities of waste. Transition metal complexes with three coordinate
pincer ligands can catalytically reduce esters using either hydrogen to produce alcohols or, reagents
such as silanes or boranes that allow for further functionalization. Ruthenium complexes are promising
catalysts because ruthenium is tolerant of many functional groups, and cheaper and more abundant
than noble metals. Ruthenium pincer complexes are excellent catalysts for the reduction of esters.
However, current ruthenium, pincer catalysts must be dissolved in a solvent making them difficult or
impossible to recover and reuse. Current solid catalysts are easier to recover and reuse, however, they
are not as efficient, and a large percentage of transition metal is wasted. We aim to chemically bond
ruthenium, pincer complexes to the surface of solid materials to make new solid, ruthenium, pincer
catalysts that can be easily recovered after the reduction of esters and will be highly efficient. In this
project, we will synthesize new, solid catalysts and test their ability to reduce esters catalytically. This
project will provide a SULI student the opportunity to gain hands-on experience in the handling of air
sensitive materials with a glovebox, performing catalytic reactions, obtaining and analyzing solution and
solid state nuclear magnetic resonance (NMR) spectroscopic data, and Fourier transform infrared (FTIR)
spectroscopy.
Mentor: Damien Culver
Research Area: Inorganic Chemistry

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and
materials. However, both of them have their limitations. Precious metals have low natural abundance
and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction
conditions, which renders the identification of active sites and the understanding of reaction
mechanisms difficult. My research group will address these limitations by developing new intermetallic
NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt
specific crystal structures as well as electronic structures different from the constituent elements.
The modified electronic structures of intermetallic compounds make them unique catalytic materials. It
has been proposed that such compounds should be treated as new “elements”, considering their
potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large
variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant
metals, to replace unstable alloy and precious metal catalysts.
Mentor: Wenyu Huang
Research Area: Inorganic Chemistry

Chemical Upcycling of Waste Plastics

Polymers are irreplaceable in the global economy, with myriad uses in packaging, construction,
transportation, electronics, and healthcare industries. However, their massive-scale manufacture,
single-use function, long lifetimes, slow decomposition rates, and disruption of sensitive ecosystems
have created a plastic waste crisis. Unfortunately, conventional mechanical recycling methods are
limited by considerable technological and economic challenges. Chemical upcycling, an emerging
alternative to the classical recycling approach, would use plastic waste as a feedstock to synthesize
value-added chemicals and materials. This project will focus on developing advanced catalysts and novel
catalytic processes that can achieve efficient and selective upcycling of waste plastics to high-value
chemicals. In particular, we want to (1) develop catalysts based on cheap and more abundant metal
elements, (2) increase the activity and selectivity of the catalytic conversion, and (3) enlarge the scale of
the conversion process.
Mentor: Wenyu Huang
Research Area: Renewable Energy Sciences and Technologies

Terahertz nanoscopy of superconducting materials evaluation in transmon qubit devices

Superconducting transmon qubit devices are one of the leading quantum computing platforms. To
advance these superconducting quantum systems, it is critical to identify and address material
imperfections that lead to decoherence. In this project, a terahertz scanning near-field optical
microscopy setup will be used to probe the local dielectric properties and carrier concentrations of
niobium resonators on silicon, one of the most characteristic components of the superconducting
quantum processors. Terahertz permittivity values will be extracted from nanospectroscopy and fitted
with the Drude model to evaluate the carrier concentrations. This near-field terahertz investigation will
provide a way to quantitatively evaluate and identify inhomogeneities in quantum devices.
Mentor: Richard Kim
Research Area: Quantum Information Science- Other

Bioengineering magnets attached to DNA origami

For a number of animals, including birds, fish and mammals, there is evidence that magnets are used for
orientation. However, little is known about how these organisms build these magnets. We have
isolated a protein from magnetotactic bacteria that will drive the formation of magnetic particles in the
test tube. We have also discovered the mechanism by which the protein makes magnets. With this new
understanding, we will use this protein to discover how we can produce magnets on engineered
surfaces to provide these surfaces with the capability of being aligned by magnetic forces. This project
involves working with proteins and mutant versions with altered activity, linking these proteins to larger
structures that are created from DNA (DNA origami) and making a variety of biochemical and biophysical
measurements of the proteins and their magnetic products. With this knowledge we can devise materials in which magnets are grown in predefined locations and to specifications of size and magnetic
character.
Mentor: Marit Nilsen-Hamilton
Research Area: Engineering Biological (nonmedical)

High performance Aluminum-Cerium (Al-Ce) Alloys for aerospace applications

Aluminum alloys are reliable lightweight and affordable materials for aerospace and engineering
applications. Earlier studies from Ameslab and others have shown that cerium addition in aluminum
increases its microstructure stability and strength retention after high temperature exposure. This
allows aluminum alloys to be used at higher temperatures and enhance their safety rating as critical
structural components. This project will focus on compositional or process development to further
improve Al-Ce alloys’ phase stability, microstructure, and tensile properties. Prospective students
interested in structural, energy-efficient, and lightweight materials are encouraged to apply. Through
this project, the students will gain hands-on knowledge on the preparation and characterization of
aluminum alloys. A potential outcome of this SULI program is a peer-reviewed paper on the structure-
performance relationship of Al-Ce alloy.
Mentor: Gaoyuan Ouyang
Research Area: Materials Science

High energy density soft magnetic materials for a sustainable future

Soft magnetic materials (SMMs) are used to enhance or guide the magnetic flux of a copper winding.
The energy density and energy efficiency of electric motors, inductors, transformers, and generators are
heavily dependent on the SMMS used in their cores. The development of advanced SMMs is the key to
the rapid boost of electric vehicles and a sustainable future. High saturation magnetization and high
electrical resistivity make an SMM attractive. Good mechanical properties and low cost are also
desirable. SMMs like high silicon steel show an excellent balance between high saturation, high
resistivity, and low cost. However, the increased silicon content makes the material brittle due to
ordering. Rapid solidification reduces the ordering, but subsequent annealing is needed to optimize the
magnetic properties. This project will investigate the role of thermomechanical processing on the
magnetic properties and mechanical properties of rapid solidified high silicon steel.
Mentor: Gaoyuan Ouyang
Research Area: Materials Science

Quantum Computing

As quantum information science (QIS) develops quantum computing architectures and storage, security
approaches will be required to create trusted platforms and execution environments. QIS can be applied
to near term utilization for security applications as well as evaluating future quantum architectures that
would not be susceptible to classical computing vulnerabilities. This project aims to collect the current
state of simulation/emulation environments including cloud services, cyber-security for quantum
computing, and cyber-security utilizing quantum algorithms. This project would then create a
framework for further quantum applications, document and create a development environment (e.g.
python, QISKIT, etc.) and demonstrate a quantum algorithm for a cyber-security application such as
random number or quantum key generation.
Mentor: Durga Paudyal
Research Area: Quantum Computing

Machine Learning

The screening of novel materials with good performance and the modeling of quantitative structure-
property relationships, among other issues, are hot topics in the field of materials science. Traditional
computational modeling often consume tremendous time and resources and are limited by their
theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery
and design process for novel materials. Recently, materials discovery and design using machine learning
have been receiving increasing attention and have achieved great improvements in both time efficiency
and prediction accuracy. Here we intend to introduce machine learning for rare earth containing
materials, propose possible algorithms to predict new materials. By directly combining computational
studies with available experimental data, we hope to provide insight into the parameters that affect the
properties of materials, thereby enabling more efficient and target oriented research on materials
discovery and design.
Mentor: Durga Paudyal
Research Area: Materials Sciences

Designing solid-state defect qubits for quantum technologies

Solid-state defects acting as single photon sources and quantum bits (qubits) are leading contenders in
quantum technologies. Despite great efforts, not all the properties and behaviors of the presently
known solid-state defect qubits are understood. Furthermore, various quantum technologies require
novel solutions, thus new solid state defect qubits should be explored to this end. These issues call to
develop ab initio methods which accurately yield the key parameters of solid-state defect qubits and
vastly accelerate the identification of novel ones for a target quantum technology application. We aim
to describe recent developments in the field including the calculation of excited states with quantum
mechanical forces, treatment of spatially extended wavefunctions in supercell models, methods for
temperature-dependent Herzberg–Teller fluorescence spectrum and photo-ionization thresholds,

accurate calculation of magneto-optical parameters of defects consisting of heavy atoms, as well as
spin-phonon interaction responsible for temperature dependence of the longitudinal spin relaxation T1
time and magneto-optical parameters, and finally the calculation of spin dephasing and spin-echo times.
We aim to design effective-mass like excited states of deep defects and understand the leading
microscopic effect in the spin relaxation of rare earth dopants in wide band gap oxide hosts.
Mentor: Durga Paudyal
Research Area: Quantum Information Science- Other

Data Science for Materials Science

Data science has drastically changed how chemical research is conducted and advanced. We would like
to introduce new methodologies of data science (artificial intelligence) and robotic high throughput
instruments to materials chemistry for catalysis and separation, which is the key in chemical and mining
industries.
In this project, new methods including simulation and modeling, and artificial intelligence will be
developed and implemented to increase the instrument efficiency and understand more of the
experimental data. Workflow with robotic high throughput instruments will be developed for different
case studies.
Mentor: Long Qi
Research Area: Computer Science and Technologies

Supported catalysts for Strong Bond Activation

Supported metal complexes are promising heterogeneous catalysts for the selective activation of strong
covalent bonds (such as C-O and C-H) in renewable feedstocks. In this project, the project participant
will work in diverse interdisciplinary areas, including organic synthesis, electrocatalysis, and materials
chemistry alongside lab scientists and postdoctoral researchers. The detailed workflow of the project is
described as below; 1) synthesize a series of organic macrocyclic - metal complexes; 2) characterize
these molecular complexes using Nuclear magnetic resonance (NMR), mass spectrometry (MS),
ultraviolet–visible spectroscopy (UV/Vis), X-ray crystallography, elemental analysis (EA), and cyclic
voltammetry (CV) techniques; 3) learn to graft these complexes onto the inorganic material surface; 4)
perform catalytic performance evaluation by setting up different reactions.
Mentor: Long Qi
Research Area: Physical Chemistry

Finding the One Fragment Method to Rule Them All Part III

Fragment-based methods are a promising means of alleviating the highly non-linear scaling of traditional
electronic structure methods. While the underlying principle is quite simple (break one large chemical
system into many smaller chemical systems), researchers have proposed a plethora of ways to do this.
Unfortunately, this makes application of fragment-based methods difficult as non-expert users
are forced to sift through the myriad of options on their own. Compounding the problem, most existing
fragment-based methods are implemented in one-off codes and are not readily accessible outside the
originating research group. To help combat these problems, we have introduced GhostFragment, an
open-source modular library capable of mixing and matching components of existing fragment-based
methods. In the previous two parts of this research we have implemented the basic GhostFragment
infrastructure, and several capping methods, this research will focus on implementing various
fragmentation methods.
Mentor: Ryan Matthew Richard
Research Area: Theoretical Chemistry

Nanostructures with Nanoparticles Functionalized with Polyethylene Oxide

Nanocrystals (NCs) are promising materials that serve as fundamental building blocks, replacing
traditional atoms or molecules, to address various technological challenges in our modern era. This
undertaking involves predicting the assembly of nanomaterials and assessing the overall stability of
these assemblies. Furthermore, it explores the potential for functional properties.
Our research group has devised several methods to comprehend and forecast the rational design of NC
materials through programmable self-assembly using DNA, electrostatic phase separation of neutral
polymers, attachment of irreversible dithiol linkers, interpolymer complexation, Nanocomposite
Tectons, and solvent evaporation.
Initially, the student will acquaint themselves with the group's diverse software packages, which are
python-based, and subsequently employ them to conduct structural predictions. A significant focus lies
in calculating free energies and comparing the stability of different structures. The specific systems
under consideration comprise of nanoparticles functionalized with polyethylene oxide polymers.
Additionally, this project involves collaborations with the ongoing FWP (Funding Work Program) on
biomineralization.
Mentor: Alex Travesset
Research Area: Materials Science

Building New solid ruthenium pincer catalysts for ester reduction

The Ames Laboratory solid-state nuclear magnetic resonance (ss-NMR) project is engaged in the
synthesis and characterization of novel nanostructures including two-dimensional semiconductors
(borophanes, high-temperature stable MXenes), semiconductor quantum dots (including CdSe/CdS),
and inorganic perovskite nanoparticles. Their properties depend critically on the surfaces of these
nanostructures including surface functionalization. NMR spectroscopy provides fascinating information
on the local environments of atoms on the surface. This project will computationally model these
nanostructures with density functional calculations, utilizing relativistic effects for heavy atoms, to
determine the chemical shifts of atoms on surfaces and how these depend on the precise geometry and
nanostructure. The modelling tools include the Materials Studio software package. The project is
expected to uncover individual atoms in these nanostructures that can explain many puzzling features of
ongoing experiments. This computational project will be jointly performed with R. Biswas and A. Rossini
at Ames National Laboratory.
Mentor: Rana Biswas
Research Area: Nanoscience

Building New solid ruthenium pincer catalysts for ester reduction

Rare-earth permanent magnets (REPMs) have excellent magnetic properties and have been widely used
in energy conversion, telecommunication, consumer electronics, biomedical devices, and magnetic
sensors. However, REPMs are brittle and cannot be used for applications subjected to high stress,
vibration, or mechanical shock. The brittleness also leads to a magnet production and machining loss of
up to 20-30% in volume and imposes limitations on part size and shape.
This project aims to produce Nd-Fe-B or Sm-Co-based sintered magnets that are mechanically stronger
than commercial products while maintaining their excellent magnetic properties and reducing the
pressure on the critical material supply chain. One of the effective strengthening approaches is to cover
the magnets with high mechanical strength and ductile metal coatings. We will develop novel metal
coatings via heterogeneous microstructure engineering for REPMs. The novel coating(s) can not only
protect the magnets from fracturing but also prevent them from corrosion and oxidization.
Mentor: Baozhi Cui
Research: Materials Sciences

Building New solid ruthenium pincer catalysts for ester reduction

Organic esters are common functional groups but are challenging to reduce. Reduction of esters
typically requires highly reactive reagents, such as lithium aluminum hydride, in stoichiometric
quantities that generate large quantities of waste. Transition metal complexes with three coordinate
pincer ligands can catalytically reduce esters using either hydrogen to produce alcohols or, reagents
such as silanes or boranes that allow for further functionalization. Ruthenium complexes are promising
catalysts because ruthenium is tolerant of many functional groups, and cheaper and more abundant
than noble metals. Ruthenium pincer complexes are excellent catalysts for the reduction of esters.
However, current ruthenium, pincer catalysts must be dissolved in a solvent making them difficult or
impossible to recover and reuse. Current solid catalysts are easier to recover and reuse, however, they
are not as efficient, and a large percentage of transition metal is wasted. We aim to chemically bond
ruthenium, pincer complexes to the surface of solid materials to make new solid, ruthenium, pincer
catalysts that can be easily recovered after the reduction of esters and will be highly efficient. In this
project, we will synthesize new, solid catalysts and test their ability to reduce esters catalytically. This
project will provide a SULI student the opportunity to gain hands-on experience in the handling of air
sensitive materials with a glovebox, performing catalytic reactions, obtaining and analyzing solution and
solid state nuclear magnetic resonance (NMR) spectroscopic data, and Fourier transform infrared (FTIR)
spectroscopy.
Mentor: Damien Culver
Research Area: Inorganic Chemistry

Novel High-Performance Permanent Magnets Development for Electric Vehicles and Generators

Novel High-Performance Permanent Magnets Development for Electric Vehicles and Generators
Are you passionate about shaping the future of electric vehicles and advanced power generation? Join
our cutting-edge research project focused on developing high-performance permanent magnets that
can revolutionize the electric motor and generator industry. Our mission is to create critical-element-
free permanent magnets with magnetic properties rivaling neodymium-based magnets, paving the way
for a more sustainable and cost-effective future in magnetic materials.

As a SULI student researcher, you'll learn how to synthesize and optimize these innovative materials.
You will gain hands-on experience with both novel techniques, such as mechanochemistry, and standard
industry practices. Your duties will involve materials characterization, refining the synthesis process, and
magnet fabrication to enhance their properties.

Throughout this project, you will immerse yourself in a multidisciplinary lab environment, working at the
intersection of chemistry, materials science, and physics. This unique opportunity will develop your
technical skills and improve your problem-solving and collaboration abilities.
Don't miss your chance to contribute to a breakthrough that could reshape the landscape of electric
vehicles and advanced power generation. Apply now to become part of this exciting research and make
a lasting impact on the future of sustainable transportation and energy!
Mentor: Ihor Hlova
Research Area: Materials Science

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and
materials. However, both of them have their limitations. Precious metals have low natural abundance
and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction
conditions, which renders the identification of active sites and the understanding of reaction
mechanisms difficult. My research group will address these limitations by developing new intermetallic
NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt
specific crystal structures as well as electronic structures different from the constituent elements.
The modified electronic structures of intermetallic compounds make them unique catalytic materials. It
has been proposed that such compounds should be treated as new “elements”, considering their
potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large
variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant
metals, to replace unstable alloy and precious metal catalysts.
Mentor: Wenyu Huang
Research Area: Nanoscience

Chemical Upcycling of Waste Plastics

Polymers are irreplaceable in the global economy, with myriad uses in packaging, construction,
transportation, electronics, and healthcare industries. However, their massive-scale manufacture,
single-use function, long lifetimes, slow decomposition rates, and disruption of sensitive ecosystems
have created a plastic waste crisis. Unfortunately, conventional mechanical recycling methods are
limited by considerable technological and economic challenges. Chemical upcycling, an emerging
alternative to the classical recycling approach, would use plastic waste as a feedstock to synthesize
value-added chemicals and materials. This project will focus on developing advanced catalysts and novel
catalytic processes that can achieve efficient and selective upcycling of waste plastics to high-value
chemicals. In particular, we want to (1) develop catalysts based on cheap and more abundant metal
elements, (2) increase the activity and selectivity of the catalytic conversion, and (3) enlarge the scale of
the conversion process.
Mentor: Wenyu Huang
Research Area: Renewable Energy Sciences and Technologies

High performance Aluminum-Cerium (Al-Ce) Alloys for aerospace applications

Aluminum alloys are reliable lightweight and affordable materials for aerospace and engineering
applications. Earlier studies from Ameslab and others have shown that cerium addition in aluminum
increases its microstructure stability and strength retention after high temperature exposure. This
allows aluminum alloys to be used at higher temperatures and enhance their safety rating as critical
structural components. This project will focus on compositional or process development to further
improve Al-Ce alloys’ phase stability, microstructure, and tensile properties. Prospective students
interested in structural, energy-efficient, and lightweight materials are encouraged to apply. Through
this project, the students will gain hands-on knowledge on the preparation and characterization of
aluminum alloys. A potential outcome of this SULI program is a peer-reviewed paper on the structure-
performance relationship of Al-Ce alloy.
Mentor: Gaoyuan Ouyang
Research Area: Materials Science

High energy density soft magnetic materials for a sustainable future

Soft magnetic materials (SMMs) are used to enhance or guide the magnetic flux of a copper winding.
The energy density and energy efficiency of electric motors, inductors, transformers, and generators are
heavily dependent on the SMMS used in their cores. The development of advanced SMMs is the key to
the rapid boost of electric vehicles and a sustainable future. High saturation magnetization and high
electrical resistivity make an SMM attractive. Good mechanical properties and low cost are also
desirable. SMMs like high silicon steel show an excellent balance between high saturation, high
resistivity, and low cost. However, the increased silicon content makes the material brittle due to
ordering. Rapid solidification reduces the ordering, but subsequent annealing is needed to optimize the
magnetic properties. This project will investigate the role of thermomechanical processing on the
magnetic properties and mechanical properties of rapid solidified high silicon steel.
Mentor: Gaoyuan Ouyang
Research Area: Materials Science

Algorithm for Automated Fitting of Complex NMR Lineshapes

Nuclear magnetic resonance (NMR) spectroscopy is a versatile tool that is used to study the structure
and dynamics of materials. In solid samples, spectral lineshapes can be complex and affected by
between 4 and 9 independent parameters, which have their own unique value for structural
investigations. At present, the fitting of these lineshapes is a laborious and manual affair requiring the
user to enter and test different parameters until suitable fits are obtained. Least-squares fitting
programs do exist, however, these are only viable once the fit is already quite reasonable due to a high
number of local minima.
In this project, we will develop a new algorithm based on simulated annealing principles to
automatically fit solid-state NMR spectral lineshapes, without the need for prior knowledge. The SULI
student will first write an implementation of the simulated annealing algorithm capable of fitting simple

Gaussian lineshapes before moving to proper solid-state NMR lineshapes. The student will also acquire
some sample solid-state NMR spectra on test samples that will subsequently be fitted using the new
algorithm.
This project is ideal for a student with some programming background and an affinity for mathematics
willing to learn about a new field of science.
Mentor: Frederic Alain Perras
Research Area: Computational Sciences

Data Science for Materials Science

Data science has drastically changed how chemical research is conducted and advanced. We would like
to introduce new methodologies of data science (artificial intelligence) and robotic high throughput
instruments to materials chemistry for catalysis and separation, which is the key in chemical and mining
industries.
In this project, new methods including simulation and modeling, and artificial intelligence will be
developed and implemented to increase the instrument efficiency and understand more of the
experimental data. Workflow with robotic high throughput instruments will be developed for different
case studies.
Mentor: Long Qi
Research Area: Material Sciences

Supported catalysts for Strong Bond Activation

Supported metal complexes are promising heterogeneous catalysts for the selective activation of strong
covalent bonds (such as C-O and C-H) in renewable feedstocks. In this project, the project participant
will work in diverse interdisciplinary areas, including organic synthesis, electrocatalysis, and materials
chemistry alongside lab scientists and postdoctoral researchers. The detailed workflow of the project is
described as below; 1) synthesize a series of organic macrocyclic - metal complexes; 2) characterize
these molecular complexes using Nuclear magnetic resonance (NMR), mass spectrometry (MS),
ultraviolet–visible spectroscopy (UV/Vis), X-ray crystallography, elemental analysis (EA), and cyclic
voltammetry (CV) techniques; 3) learn to graft these complexes onto the inorganic material surface; 4)
perform catalytic performance evaluation by setting up different reactions.
Mentor: Long Qi
Research Area: Organic Chemistry

Simulations for Nanoparticles with in Polyethylene ligands Water Solutions

Materials whose fundamental units are nanocrystals (NC)s are major candidates to solve many of the technological challenges . In this SULI experience, the student will be involved in predicting the assembly of nanoparticles with new structural or functional properties. My group has developed different approaches to understand and predict the rational design of NC materials by programmable self-assembly through DNA, electrostatic phase separation of neutral polymers, attachment of irreversible dithiol linkers, interpolymer complexation, Nanocomposite Tectons and also, via solvent evaporation. The student will initially become familiar with the different software developed in the group and then use it to perform structural predictions. The concrete systems consist of nanoparticles functionalized with polyethylene oxide polymers and their interactions with anions and cations, such as NaCl, will be the main focus. Collaborations with the ongoing FWP, where experiments on these systems are performed, is part of this activity.

Mentor: Alex Travesset

Research Area: Materials Science

Mechanically Robust High Magnetic Performance Rare-earth Permanent Magnets

Rare-earth permanent magnets (REPMs) have excellent magnetic properties and have been widely used in energy conversion and storage, telecommunication, consumer electronics, biomedical devices, and magnetic sensors. However, REPMs are brittle and cannot be used for applications subjected to high stress, vibration, or mechanical shock. The brittleness also leads to a magnet production loss of up to 20-30% in volume and imposes limitations on part size and shape. This project aims to produce Nd-Fe-B or Sm-Co-based sintered magnets that are mechanically stronger than commercial products while maintaining or even enhancing their excellent magnetic properties. The novel mechanically strengthened high magnetic performance REPMs will be more cost-effective, efficient, and robust for energy-related applications while reducing the pressure on the critical material supply chain.

Mentor: Baozhi Cui

Research Area: Materials Science

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements”, considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Mentor: Wenyu Huang

Research Area: Inorganic Chemistry

Chemical Upcycling of Waste Plastics

Polymers are irreplaceable in the global economy, with myriad uses in packaging, construction, transportation, electronics, and healthcare industries. However, their massive-scale manufacture, single-use function, long lifetimes, slow decomposition rates, and disruption of sensitive ecosystems have created a plastic waste crisis. Unfortunately, conventional mechanical recycling methods are limited by considerable technological and economic challenges. Chemical upcycling, an emerging alternative to the classical recycling approach, would use plastic waste as a feedstock to synthesize value-added chemicals and materials. This project will focus on developing advanced catalysts and novel catalytic processes that can achieve efficient and selective upcycling of waste plastics to high-value chemicals. In particular, we want to (1) develop catalysts based on cheap and more abundant metal elements, (2) increase the activity and selectivity of the catalytic conversion, and (3) enlarge the scale of the conversion process.

Mentor: Wenyu Huang

Research Area: Renewable Energy Sciences and Technologies

Control catalysis and separation at atomic and electronic-level using metal-organic frameworks

Catalysis and separation are two of the most important chemical industry processes. Control catalysis and separation at the atomic and electronic level represents one of the most challenging research areas. Using metal-organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. In separation, we can tune molecule-MOF interactions with sub-angstrom precision to achieve a more selective and efficient separation process. MOFs are novel porous materials with great potential for catalysis and separation due to their structural diversity, flexibility, and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at the atomic level by using different organic linkers and metal nodes. The MOFs with isoreticular structures are fascinating because they have exactly the same lattice structure but different chemical compositions. These different organic linkers or metal ion nodes of MOFs result in geometrically identical cages of different chemical environments, which provide ideal platforms to systematically study catalysis and separation science.

Mentor: Wenyu Huang

Research Area: Nanoscience

Deciphering the Structure of Bronsted Sites in Silica-Alumina

Bronsted acid catalysts are of critical importance in many industrial processes. Perhaps chief among them is their use to catalyze dehydroaromatization and rearrangements of hydrocarbons to make products such as benzene, toluene, and xylene. The most well-understood Bronsted catalysts are zeolites, where the acid sites are known to be Si-OH-Al bridging acid sites. The structure of the acid sites in amorphous silica-aluminas, however, is not well understood and is a subject of some controversy. One hypothesis states that they take the same form as the bridging sites in zeolites while others have proposed that they are rather pseudo-bridging sites composed of a silanol in proximity to an aluminum center with an open coordination site, i.e: Si-OH·····Al.

We will use NMR spectroscopy, and a clever labelling strategy, to solve this conundrum. Specifically, we will deuterate all hydroxyl hydrogen atoms with D2O and then protonate the most acidic ones by exchanging them with the hydrogen atoms in benzene. We will then use dynamic nuclear polarization to perform a 1H-17O-27Al triple-resonance NMR experiment to measure the distance between the acidic hydroxyl hydrogen and the aluminum atom nearby. By measuring this distance we will determine whether there is a bond between the two, or whether the pseudo-bridging model is correct.

A SULI student working on this project will get hands-on lab experience in the surface preparation of materials, the in-situ study of catalysts using NMR spectroscopy, and advanced solid-state NMR methods using dynamic nuclear polarization. This is a great project for someone looking to do some puzzle solving.

Mentor: Frederic Alain Perras

Research Area: Physical Chemistry

Finding the One Fragment Method to Rule Them All

A large part of chemistry is finding chemicals with desired properties. Historically, this has been done by leveraging chemical intuition to guide experiment design. This somewhat ad hoc approach is time consuming, expensive, and potentially dangerous. Computational chemistry strives to simulate experimental chemistry in order to offer a cheaper, safer means of experiment design. Unfortunately, the computational cost of high-accuracy computational chemistry simulations limits such simulations to very small molecules (i.e. on the order of 20 atoms). Our research explores ways in which we can reduce the computational cost of such simulations, without compromising accuracy. In particular, we are very interested in fragment-based methods which, as the name suggests, break large intractable chemical systems up in to more manageable pieces, i.e. fragments. By properly modeling the interactions among fragments, it is theoretically possible to dramatically reduce the computational cost of the simulation, without compromising accuracy. In practice, fragment-based methods contain a large number of parameters, and finding an optimal set of parameters is an unsolved problem. This research project will explore the parameter space for fragment-based methods.

Mentor: Ryan Matthew Richard

Research Area: Theoretical Chemistry

Investigation of Caloric Refrigeration Concepts

Caloric materials change temperature in response to externally applied fields (magnetic, stress, electric) and are very promising for replacing conventional vapor-compression systems in cooling applications. Caloric refrigeration has the potential to improve efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of caloric technologies for cooling. The research project will focus on demonstrating early-stage cooling concepts using magnetocaloric and elastocaloric materials.

Mentor: Julie Slaughter

Research Area: Engineering Materials

Computational Studies of Interactions among Nanocrystals

Materials consisting of nanocrystals (NC)s as building blocks, as opposed to atoms or molecules, are major candidates to solve a number of the technological challenges of our times. In this activity, the student will be involved in predicting how NC interact in water. More concretely, we will study how attraction among nanocrystals may be induced by electrolytes (salt). For that purpose, we will consider gold cores functionalized with polyethylene glycol and analyze how hydrogen bonds are affected by the present of different salts. Our group has already developed software packages that greatly facilitate these calculations, so the student will be able to get productive very quickly. Familiarity with Python will facilitate a more rapid adaptation, but it can be learned during the internship. Collaborations with the ongoing FWP on biomineralization at the Ames lab, where actual experiments are being performed, is part of this activity.

Mentor: Alex Travesset

Research Area: Nanoscience

Computational Assembly of Novel Perovskite Nanocrystal Cubes

"Materials consisting of nanocrystals (NC)s as building blocks, as opposed to atoms or molecules, are major candidates to solve a number of the technological challenges of our times. In this activity, the student will be involved in predicting how a new type of nanocrystals, whose shape is a cube will be investigated. We will also explore the overall stability of these assemblies with and without solvent. We will compute the free energy of interaction for small nanocubes and predict the ordered arrangement with the lowest free energy.

My group has developed a number of software packages in python, which enable to run molecular dynamics and analyze the data, so the students will be able to benefit from all this infrastructure and in this way, be productive right away. Familiarity with python is a plus, but can be learnt on the site."

Mentor: Alex Travesset

Research Area: Nanoscience

Tracking dynamics of magnetic topological states

Magnetic topological states, such as skyrmions, are nanoscale vortex-like swirling spin objects that have attracted considerable interest as information carriers for future spintronic devices. Lorentz transmission electron microscopy (LTEM) allows us to observe magnetic topological states directly in real-space with nanometer resolution. This research project will study the kinetics of magnetic topological states using in-situ LTEM. The student will be involved in LTEM image analysis and data processing.

Mentor: Lin Zhou

Research Area: Quantum Materials

Novel nanostructures - making each atom count

The Ames National Laboratory solid-state nuclear magnetic resonance (SS-NMR) project is engaged in the synthesis and characterization of novel nanostructures including two-dimensional semiconductors (silicon nanosheets, borophanes, high-temperature stable MXenes), semiconductor quantum dots (including CdSe/CdS/PbSe), amd inorganic perovskite nanoparticles. The properties of these low dimensional structures are markedly different from their bulk counterparts and depend sensitively on where the atoms are located- especially on the surface. NMR spectroscopy provides fascinating information on the local environments of atoms on the surface. This project will computationally model these nanostructures with density functional calculations, utilizing relativistic effects for heavy atoms, to determine the chemical shifts of atoms on surfaces and how these depend on the precise geometry and nanostructure. The project is expected to uncover novel atomistic models for nanostructures that can explain many puzzling features of ongoing experiments. The project will be performed in collaboration with SS-NMR group members.

Mentor: Rana Biswas

Research Area: Nanoscience

Synthetic Microbial Communities for Exploring Plant-Microbe Interactions

The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. We are interested in developing a deeper understanding of how plants interact with beneficial microbes in the rhizosphere. This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes (e.g., quorum-sensing, or competitive or stimulatory) but also with plants themselves. This project will contribute to the development and validation of an instrument for detecting molecules secreted by microbes. This devise relies on nucleic acid-based sensors integrated into mobile probes to send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). Our contribution is to develop a synthetic microbial community for assessing the efficacy of our imaging system while providing insight into the dynamics and fate of the targeted chemicals in the rhizosphere. We will develop synthetic biology tools for controlling production of targeted metabolites by one microbe and separate tools for detecting targeted metabolites by another. CRISPR interference is used to modulate expression of the targeted secreted metabolites and other essential genes in various Pseudomonas species that are model rhizosphere colonists. For this we use a “plug-and-play” synthetic microbial community to assess how the presence of signal molecule consumers and how species complexity influences production of the secreted metabolite and how signal production influence fitness (growth and competitiveness) in the rhizosphere.

Mentor: Larry Halverson

Research Area: Molecular Biology

High performance Aluminum-Cerium (Al-Ce) Alloys for aerospace applications

Aluminum alloys are reliable lightweight and affordable materials for aerospace and engineering applications. Earlier studies from Ameslab and others have shown that cerium addition in aluminum increases its microstructure stability and strength retention after high temperature exposure. This allows aluminum alloys to be used at higher temperatures and enhance their safety rating as critical structural components. This project will focus on compositional or process development to further improve Al-Ce alloys’ phase stability, microstructure, and tensile properties. Prospective students interested in structural, energy-efficient, and lightweight materials are encouraged to apply. Through this project, the students will gain hands-on knowledge on the preparation and characterization of aluminum alloys. A potential outcome of this SULI program is a peer-reviewed paper on the structure-performance relationship of Al-Ce alloy.

Mentor: Gaoyuan Ouyang

Research Area: Engineering Materials

High energy density soft magnetic materials for a sustainable future

Soft magnetic materials (SMMs) are used to enhance or guide the magnetic flux of a copper winding. The energy density and energy efficiency of electric motors, inductors, transformers, and generators are heavily dependent on the SMMS used in their cores. The development of advanced SMMs is the key to the rapid boost of electric vehicles and a sustainable future. High saturation magnetization and high electrical resistivity make an SMM attractive. Good mechanical properties and low cost are also desirable. SMMs like high silicon steel show an excellent balance between high saturation, high resistivity, and low cost. However, the increased silicon content makes the material brittle due to ordering. Rapid solidification reduces the ordering, but subsequent annealing is needed to optimize the magnetic properties. This project will investigate the role of thermomechanical processing on the magnetic properties and mechanical properties of rapid solidified high silicon steel.

Mentor: Gaoyuan Ouyang

Research Area: Engineering Materials

Catalytic Upcycling of Polyolefins

The large amount of plastic waste that is produced each year ends up in landfills and in the ocean, as a result of limited end-of-life opportunities. We are discovering new catalytic reactions, synthesizing new catalysts, and developing new catalytic processes for the conversion of these discarded materials into 'upcycled' products. The project will entail catalyst synthesis, reactor construction and modification, catalytic conversion, and product analysis.

Mentor: Aaron David Sadow

Research Area: Inorganic Chemistry

Organometallic Catalyst Synthesis and Catalytic Reactions

We are synthesizing new organometallic compounds for catalysis. This involves organic chemistry, to create the ligand, and then coordination chemistry to make organometallic complexes. Then, the complexes are characterized by advanced spectroscopic methods, such as NMR, IR, and crystallography. Then, we study catalytic transformations. We are particularly interested in main group and lanthanide metal complexes for CH bond activations, to convert hydrocarbons into more valuable products.

Mentor: Aaron David Sadow

Research Area: Inorganic Chemistry

Investigation of Caloric Refrigeration Concepts

Caloric materials change temperature in response to externally applied fields (magnetic, stress, electric) and are very promising for replacing conventional vapor-compression systems in cooling applications. Caloric refrigeration has the potential to improve efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of caloric technologies for cooling. The research project will focus on demonstrating early-stage cooling concepts using magnetocaloric and elastocaloric materials.

Mentor: Julie Slaughter

Research Area: Engineering Materials

Molecular Modeling of Deep Eutectic Solvents for CO2 Removal

Deep eutectic solvents (DESs) have become popular as a promising candidate for diverse applications, e.g., extraction of natural compounds, catalysis, and carbon dioxide capture. They are also considered as green solvents since each DES component is inexpensive and environmentally benign. However, the understanding of DES remains elusive. In this project, we aim to extract key interactions between each component of DES by using quantum chemical-based calculations. The outcome of this study will provide a better understanding of solute-solvent interactions and aid in the development of DES for carbon capture.

We believe that students from a variety of backgrounds, ranging from math, computer science to physics, chemistry or biology can all benefit from the project. During the project, the student will learn a range of techniques from utilizing molecular modeling to analyzing intermolecular interactions of novel solvents.

Mentor: Tosaporn Sattasathuchana

Research Area: Theoretical Chemistry

4DMaps Sensor

Project will address the challenge of monitoring the physiology and inteactions of plants with other organisms in soil and their responses to the chemical and microbial composition of the rhizosphere. We will develop a network of aptamer functionalized sensors to monitor the chemicals excreted by plant roots and their interactions with surrounding soil. The students will design, fabricate and characterize sensors that will be used in the soil monitoring. Nanoporous alumina membranes have become a ubiquitous biosensing platform for a variety of applications and aptamers are being increasingly utilized as recognition elements in protein sensing devices. Combining the advantages of the two, we will utilize the aptamer functionalized alumina membranes for label-free sensitive detection of small molecules using a four-electrode electrochemical cell. An arduino based reader will be developed to monitor the impedance of the alumina membrane in the four electrode cell configuration.

Mentor: Pranav Shrotriya

Research Area: Nanoscience

Mechanically Robust High Magnetic Performance Nd-Fe-B Sintered Magnets

Rare-earth permanent magnets (REPMs) have excellent magnetic properties and have been widely used in energy conversion and storage, telecommunication, consumer electronics, biomedical devices, and magnetic sensors. However, REPMs are brittle and cannot be used for applications subjected to high stress, vibration, or mechanical shock. The brittleness also leads to a magnet production loss of up to 20-30% in volume and imposes limitations on part size and shape. This project is to produce Nd-Fe-B based sintered magnets mechanically stronger than the commercial products while maintaining their excellent magnetic properties. The new mechanical strengthening approaches and mechanisms will be studied by both experimental work and theoretical modeling. The novel mechanically strengthened high magnetic performance Nd-Fe-B magnets will be more cost-effective, efficient, and robust for energy-related applications while reducing the pressure on the critical material supply chain.

Mentor: Baozhi Cui

Research Area: Engineering Materials

Bacterial cell-cell communication in the rhizosphere: genetic tools to control production of secreted public goods

The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. We are interested in developing a deeper understanding of how plants interact with beneficial microbes in the rhizosphere. To establish a root-associated microbiome requires the ability of microbes to communicate with each other by chemical signals that they secrete. This project will contribute to the development and validation of an instrument for detecting molecules secreted by microbes. This devise relies on nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform to send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). To ensure that the aptasensor works properly and to assess the role of secreted metabolites on root colonization, we are using CRISPR interference to modulate, or knockdown, expression of the targeted secreted metabolites in various Pseudomonas species that are model rhizosphere colonists. For this we use a “plug-and-play” synthetic microbial community to assess how the presence of signal molecule consumers and how species complexity influences production of the secreted metabolite and how signal production influence fitness (growth and competitiveness) in the rhizosphere.

Mentor: Larrry Halverson

Research Area: Molecular Biology

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements”, considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Mentor: Wenyu Huang

Research Area: Inorganic Chemistry

Control heterogeneous catalysis at atomic and electronic-level using metal-organic frameworks

To control heterogeneous catalysis at the atomic and electronic level represents one of the most challenging research areas. Using metal-organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal nanoclusters, have great potentials for catalysis due to their structural diversity, flexibility, and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at the atomic level by using different organic linkers. The MOFs with isoreticular structures are fascinating because they have exactly the same lattice structure but different chemical compositions. These different organic linkers or metal ion nodes of MOFs result in geometrically identical cages of different chemical environments. Nanoclusters confined in these cages/cavities would experience an atomic-level fine-tuned chemical environment, and thus exhibit different activity and selectivity in heterogeneous catalysis. During chemical conversion processes, reactants and reaction intermediates could also sense these chemical environments that could alter their adsorption energy and geometry, which will also affect the reaction activity and selectivity.

Mentor: Wenyu Huang

Research Area: Materials Science

Chemical Upcycling of Waste Plastics

Polymers are irreplaceable in the global economy, with myriad uses in packaging, construction, transportation, electronics, and healthcare industries. However, their massive-scale manufacture, single-use function, long lifetimes, slow decomposition rates, and disruption of sensitive ecosystems have created a plastic waste crisis. Unfortunately, conventional mechanical recycling methods are limited by considerable technological and economic challenges. Chemical upcycling, an emerging alternative to the classical recycling approach, would use plastic waste as a feedstock to synthesize value-added chemicals and materials. This project will focus on developing advanced catalysts and novel catalytic processes that can achieve efficient and selective upcycling of waste plastics to high-value chemicals. In particular, we want to (1) develop catalysts based on cheap and more abundant metal elements, (2) increase the activity and selectivity of the catalytic conversion, and (3) enlarge the scale of the conversion process.

Mentor: Wenyu Huang

Research Area: Renewable Energy Sciences and Technologies

On-surface synthesis of atomically precise nanographenes from molecular precursors

Atomically precise synthesis methods have critical role in advancing capabilities of solar energy harvesting, electrical energy storage, catalysis, solid state lighting, carbon capture, and quantum materials.

In the project, we will develop and apply on-surface molecular-based synthesis methods for fabrication of novel low-dimensional nanomaterials. The synthesis processes will rely on predesigned organic molecular precursors, which, after deposition on crystalline substrates, undergo a series of programmed chemical reactions leading to atomically defined nanographene architectures. Due to atomic perfection in the resulting morphology, this approach allows property-driven control over unique electronic, magnetic, optical, and transport properties of the resulting nanomaterials.

The experiments will be performed under well-defined ultra-high vacuum conditions, i.e. preparation of surfaces, precursor deposition and activation as well as main part of characterization will be performed in-situ without breaking the vacuum. To locally monitor the single precursor molecules, intermediates, and products, we will use scanning probe microscopy-based methods supported by complementary surface science techniques including photoelectron spectroscopy, low energy electron diffraction and mass spectroscopy.

Mentor: Marek Kolmer

Research Area: Nanoscience

Potentials and Free Energy Calculations in Nanoparticle Structure Prediction

Materials consisting of nanocrystals (NC)s as building blocks, as opposed to atoms or molecules, are major candidates to solve a number of the technological challenges of our times. In this activity, the student will be involved in predicting how nanomaterials assemble and the overall stability of these assemblies. In addition, the possibility of functional properties will be exploted. My group has developed different approaches to understand and predict the rational design of NC materials by programmable self-assembly through DNA, electrostatic phase separation of neutral polymers, attachment of irreversible dithiol linkers, interpolymer complexation, Nanocomposite Tectons and also, via solvent evaporation. The student will initially become familiar with the different software packages developed in the group, which operate through python, and then use it to perform structural predictions. Particular emphasis is the calculation of free energies and comparison of the stability for different structures.The concrete systems consist of nanoparticles functionalized with polyethylene oxide polymers. Collaborations with the ongoing FWP on biomineralization is part of this activity.

Mentor: Alex Travesset

Research Area: Materials Sciences

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements”, considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Research area: Nanoscience
Mentor: Wenyu Huang

Chemical Upcycling of Waste Plastics

Polymers are irreplaceable in the global economy, with myriad uses in packaging, construction, transportation, electronics, and healthcare industries. However, their massive-scale manufacture, single-use function, long lifetimes, slow decomposition rates, and disruption of sensitive ecosystems have created a plastic waste crisis. Unfortunately, conventional mechanical recycling methods are limited by considerable technological and economic challenges. Chemical upcycling, an emerging alternative to the classical recycling approach, would use plastic waste as a feedstock to synthesize value-added chemicals and materials. This project will focus on developing advanced catalysts and novel catalytic processes that can achieve efficient and selective upcycling of waste plastics to high-value chemicals. In particular, we want to (1) develop catalysts based on cheap and more abundant metal elements, (2) increase the activity and selectivity of the catalytic conversion, and (3) enlarge the scale of the conversion process.

Research Area: Renewable Energy Sciences and Technologies
Mentor: Wenyu Huang

Control heterogeneous catalysis at atomic and electronic-level using metal-organic frameworks

To control heterogeneous catalysis at the atomic and electronic level represents one of the most challenging research areas. Using metal-organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal nanoclusters, have great potentials for catalysis due to their structural diversity, flexibility, and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at the atomic level by using different organic linkers. The MOFs with isoreticular structures are fascinating because they have exactly the same lattice structure but different chemical compositions. These different organic linkers or metal ion nodes of MOFs result in geometrically identical cages of different chemical environments. Nanoclusters confined in these cages/cavities would experience an atomic-level fine-tuned chemical environment, and thus exhibit different activity and selectivity in heterogeneous catalysis. During chemical conversion processes, reactants and reaction intermediates could also sense these chemical environments that could alter their adsorption energy and geometry, which will also affect the reaction activity and selectivity.

Research Area: Inorganic Chemistry
Mentor: Wenyu Huang

On-surface synthesis of atomically precise low-dimensional materials

Atomically precise synthesis methods have critical role in advancing capabilities of solar energy harvesting, electrical energy storage, catalysis, solid state lighting, carbon capture, and quantum materials.

In the project, we will develop and apply on-surface molecular-based synthesis methods for fabrication of novel low-dimensional nanomaterials. The synthesis processes will rely on predesigned molecular precursors, which, after deposition on crystalline substrates, undergo a series of programmed chemical reactions leading to atomically defined nanographene architectures. Due to atomic perfection in the resulting morphology, this approach allows property-driven control over unique electronic, magnetic, optical, and transport properties of the resulting nanomaterials.

The experiments will be performed under well-defined ultra-high vacuum conditions, i.e. preparation of surfaces, precursor deposition and activation as well as main part of characterization will be performed in-situ without breaking the vacuum. To locally monitor the single precursor molecules, intermediates, and products, we will use scanning probe microscopy-based methods supported by complementary surface science techniques including photoelectron spectroscopy, low energy electron diffraction and mass spectroscopy.

Mentor: Marek Kolmer

Research Area: Nanoscience

Mechanically Strengthened High Magnetic Performance Rare-earth Permanent Magnets

Rare-earth permanent magnets (REPMs) have excellent magnetic properties and have been widely used in energy conversion and storage, telecommunication, consumer electronics, biomedical devices, and magnetic sensors. However, REPMs are brittle and cannot be used for applications subjected to high stress, vibration, or mechanical shock. The brittleness also leads to magnet production loss up to 20-30% in volume and imposes limitations on part size and shape. This project is to produce REPMs (mainly Nd-Fe-B and Sm-Co sintered magnets) mechanically stronger than the commercial products while maintaining their excellent magnetic properties and reducing magnet waste rate to less than 10%. Especially, the new mechanical strengthening approaches and mechanisms will be studied by both experimental work and theoretical modeling. The novel mechanically strengthened high magnetic performance REPMs will be more cost-effective, efficient, and robust for energy-related applications while reducing the pressure on the critical material supply chain.
Research area: Materials Sciences
Mentor: Baozhi Cui

Synthetic Microbial Communities for Exploring Plant-Microbe Interactions

We are interested in developing a deeper understanding of how plants interact with both beneficial and detrimental microbes in the rhizosphere. The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes (e.g., quorum-sensing, or competitive or stimulatory) but also with plants themselves. This project will build a testbed for a new instrument for detecting specific molecules produced by microbes or the plant in the rhizosphere. These nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform will send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). Our contribution is to develop a synthetic microbial community for assessing the efficacy of our imaging system while providing insight into the dynamics and fate of the targeted chemicals in the rhizosphere. We will develop synthetic biology tools for controlling production of targeted metabolites by one microbe and separate tools for detecting targeted metabolites by another. Through the construction of a “plug-and-play” synthetic community modelled on the natural maize rhizosphere microbiome, we will increase community complexity, including the introduction of natural producers and consumers of the targeted metabolites.

Mentor: Larrry Halverson

Research Area: Molecular Biology

Isolating aptamer receptors for rhizosphere sensing

The rhizosphere is a thin layer around the roots of a plant where microbes congregate. Some microbes are beneficial and others pathogenic. Plants need microbes in the rhizosphere for their proper nutrition. So, they do things to attract the beneficial microbes. For example, up top 70% of a plant's energy can be excreted through the roots into the surrounding rhizosphere to feed the microbes, some of which convert nitrogen gas into forms like ammonium that can be absorbed by the plant. We are interested in understanding this mutualistic relationship as it occurs in the soil. We are also interested in understanding how plants interact with harmful microbes that sometimes enter the rhizosphere. To gain this understanding, we need to obtain data on the molecular signals by which plants and microbes interact. This project is to build the parts of a new instrument for sensing specific molecules in the rhizosphere. The part we are focusing on first is to build the sensors that will be used to detect the molecules. These sensors will send signals to a central computer which will create a 3D image of the distribution of this chemical around the root over time (4D). To build the sensors we will be selecting and maturing nucleic acid aptamers that specifically recognize the molecules of interest. Similar in their function to antibodies, aptamers have properties that are much more applicable to functioning underground than do antibodies. Once selected and matured, the aptamers will be integrated into a nanoporous anodized aluminum oxide sensing platform to create a sensor that will be placed at the tips of the instrument to be placed in the soil for molecular recognition.

Mentor: Marit Nilsen-Hamilton

Research Area: Biochemistry

Quantum Computing

As quantum information science (QIS) develops quantum computing architectures and storage, security approaches will be required to create trusted platforms and execution environments. QIS can be applied to near term utilization for security applications as well as evaluating future quantum architectures that would not be susceptible to classical computing vulnerabilities. This project aims to collect the current state of simulation/emulation environments including cloud services, cyber-security for quantum computing, and cyber-security utilizing quantum algorithms. This project would then create a framework for further quantum applications, document and create a development environment (e.g. python, QISKIT, etc.) and demonstrate a quantum algorithm for a cyber-security application such as random number or quantum key generation.
Research area: Materials Sciences
Mentor: Durga Paudyal

Machine Learning

The screening of novel materials with good performance and the modeling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modeling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.
Research area: Materials Sciences
Mentor: Durga Paudyal

Electronic structure

The rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements. Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.
Research area: Materials Sciences
Mentor: Durga Paudyal

Prediction of Nanoparticle Assemblies into Ordered Arrays

Materials whose fundamental units are nanocrystals (NC)s, instead of atoms or molecules, are emerging as major candidates to solve many of the technological challenges of our century. In this activity, the student will be involved in in predicting nanomaterials with new structural or functional properties and characterizing the right experimental conditions for successful assembly. My group has developed different approaches to understand and predict the rational design of NC materials by programmable self-assembly through DNA, electrostatic phase separation of neutral polymers, attachment of irreversible dithiol linkers, interpolymer complexation, Nanocomposite Tectons and also, via solvent evaporation. The student will initially become familiar with the different software developed in the group and then use it to perform structural predictions. The concrete systems consist of nanoparticles functionalized with polyethylene oxide polymers. Collaborations with the ongoing FWP on biomineralization is part of this activity.

Mentor: Alex Travesset

Research Area: Materials Sciences

Finding the One Fragment Method to Rule Them All

A large part of chemistry is finding chemicals with desired properties. Historically, this has been done by leveraging chemical intuition to guide experiment design. This somewhat ad hoc approach is time consuming, expensive, and potentially dangerous. Computational chemistry strives to simulate experimental chemistry in order to offer a cheaper, safer means of experiment design. Unfortunately, the computational cost of high-accuracy computational chemistry simulations limits such simulations to very small molecules (i.e. on the order of 20 atoms). Our research explores ways in which we can reduce the computational cost of such simulations, without compromising accuracy. In particular, we are very interested in fragment-based methods which, as the name suggests, break large intractable chemical systems up in to more manageable pieces, i.e. fragments. By properly modeling the interactions among fragments, it is theoretically possible to dramatically reduce the computational cost of the simulation, without compromising accuracy. In practice, fragment-based methods contain a large number of parameters, and finding an optimal set of parameters is an unsolved problem. This research project will explore the parameter space for fragment-based methods.

Mentor: Ryan Matthew Richard

Research Area: Computational Sciences

High performance Aluminum-Cerium (Al-Ce) Alloys for aerospace applications

Aluminum alloys are reliable lightweight and affordable materials for aerospace and other engineering applications. Earlier studies from Ames lab and others have shown that cerium addition in aluminum increases its microstructure stability and strength retention after high temperature exposure. This allows aluminum alloys to be used at higher temperatures and enhance their safety rating as critical structural components. This project will focus on compositional or process development to further improve Al-Ce alloys’ phase stability, microstructure, and tensile properties. Prospective students interested in structural, energy-efficient, and lightweight materials are encouraged to apply. Through this project, the students will gain hands-on knowledge on the preparation and characterization of aluminum alloys. A potential outcome of this SULI program is a peer-reviewed paper on the structure-performance relationship of Al-Ce alloy.

Mentor: Gaoyuan Ouyang

Research Area: Material Sciences

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements”, considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Research area: Nanoscience
Mentor: Wenyu Huang

Chemical Upcycling of Waste Plastics

Polymers are irreplaceable in the global economy, with myriad uses in packaging, construction, transportation, electronics, and healthcare industries. However, their massive-scale manufacture, single-use function, long lifetimes, slow decomposition rates, and disruption of sensitive ecosystems have created a crisis of plastics waste. Unfortunately, conventional mechanical recycling methods are limited by considerable technological and economic challenges. Chemical upcycling, an emerging alternative to the classical recycling approach, would use plastic waste as a feedstock to synthesize value-added chemicals and materials. This project will focus on developing advanced catalysts that can achieve efficient and selective upcycling of waste plastics to high-value chemicals.

Research Area: Renewable Energy Sciences and Technologies
Mentor: Wenyu Huang

Control heterogeneous catalysis at atomic and electronic-level using metal-organic frameworks

To control heterogeneous catalysis at the atomic and electronic level represents one of the most challenging research areas. Using metal-organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal nanoclusters, have great potentials for catalysis due to their structural diversity, flexibility, and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at the atomic level by using different organic linkers. The MOFs with isoreticular structures are fascinating because they have exactly the same lattice structure but different chemical compositions. These different organic linkers or metal ion nodes of MOFs result in geometrically identical cages of different chemical environments. Nanoclusters confined in these cages/cavities would experience an atomic-level fine-tuned chemical environment, and thus exhibit different activity and selectivity in heterogeneous catalysis. During chemical conversion processes, reactants and reaction intermediates could also sense these chemical environments that could alter their adsorption energy and geometry, which will also affect the reaction activity and selectivity.

Research Area: Inorganic Chemistry
Mentor: Wenyu Huang

EPR studies of photogenerated spin-active defects in organic photovoltaic materials

Even though efficiencies over 18% have been reported for Organic Photovoltaics (OPVs), stability remains the foremost challenge for commercialization. The OPVs are known to degrade under the presence of oxygen, moisture, and E/M radiation. While degradation due to oxygen and moisture can be eliminated by encapsulation, photodegradation remains a major issue. This project will study the photodegradation mechanisms in OPVs, specifically non-fullerene acceptor (NFA) based OPVs. Such a study is necessary to understand the basics of photodegradation processes and develop innovative strategies to overcome stability issues. The photogenerated defects will be studied primarily by electron paramagnetic resonance (EPR). This project will include sample preparation, including UV irradiation of films in vacuum-sealed quartz tubes, and EPR measurements and analysis. The EPR measurements will be performed at cryogenic temperatures to provide insight into the nature of the defects and possible technological applications.

Research Area: Renewable Energy Sciences and Technologies
Mentor: Joseph Shinar

Role of short-range order on mechanical behavior of high-entropy alloys

Order–disorder transformations hold an essential place in chemically complex alloys due to their critical technological application. The chemical inhomogeneity arising from mixing of multi-principal elements in an alloy of varying chemistry can drive property altering changes at the atomic scale, in particular short-range order (SRO). Despite the SRO being a key structural feature of chemically complex alloys, its role on mechanical behavior finds limited understanding. Tuning the degree of SRO can be an effective way for optimizing mechanical properties of chemically complex alloys. Thus, understanding the role of SRO through computational investigation on mechanical behavior can provide critical information regarding future design rules for technologically useful materials. Additionally, the challenges concerning formation and characterization of SROs will be explored, and future research activities involving SRO in electronic and physical properties of technologically critical alloys will be critically assessed.

Research Area: Materials Sciences
Mentor: Prashant Singh

Synthesis and Spectroscopy of Alkaline-Earth Chalcogenide Nanocrystals

With an increased demand for effective semiconducting materials, it is important to focus on compositions containing earth-abundant and biocompatible elements. Alkaline-earth chalcogenides (IIa-VIb) have been utilized over the last decades as practical materials for optical applications, mainly due to their enhanced luminescence when doped with rare earth ions. They have also been predicted to exhibit favorable thermoelectric properties in both their rock salt and hexagonal monolayer forms. In addition to their wide-ranging optical properties, alkaline-earth materials utilize earth-abundant and biocompatible elements, which makes them advantageous alternatives compared to other toxic heavy metal chalcogenides. This project will look at the preparation of these materials as colloidal nanocrystals using solution-phase reactions. The new materials will be characterized by X-ray diffraction and spectroscopy methods.

While current synthetic approaches for producing alkaline-earth chalcogenide compositions are effective, there are still some fundamental gaps in the knowledge of IIa-VIb systems. Most of the current syntheses have been developed for monochalcogenide compositions, and their parent (undoped) compositions are significantly less studied, particularly regarding their phase evolution and nucleation. Many synthetic pathways are also limited to producing only a single IIa-VIb phase, and few have demonstrated selectivity between different mono- and polychalcogenide compositions. In addition to limited phase control, few methods have effectively shown particle size tunability, often producing either bulk material or select crystalline sizes. Therefore, there is great merit in developing colloidal syntheses that allow high levels of control over phase purity, particle size, and even optical properties, for various alkaline-earth sulfide and selenide compositions.

Research Area: Nanoscience
Mentor: Javier Vela

Epitaxy and Ion Exchange on Colloidal Pyrite Nanocrystals

Pyrite (FeS2) has been a material of international research interest for decades due to its natural abundance, low toxicity, and possession of a bandgap that makes it suitable for a wide range of applications, such as photovoltaics and energy storage. The pyrite phase (Pa ) is not just limited to iron, nor to sulfur. Many metal chalcogenides adopt this cubic crystal structure – e.g., MnS2, MnSe2, CoS2, NiSe2, etc. There exist, however, the impeding challenge of eliminating persistent impurities like the commonly seen marcasite polymorph (Pmnn). While the previously mentioned pyrite-type materials have been made and treated through several different methods, there is still a wide margin of opportunity for research on morphological effects on catalytic ability, alloying and construction of heterostructures, and phase transformations, to name a few fields. Additionally, metastable pyrite phases hold a well of untapped potential that could serve as springboards for more efficient devices. For example, ZnS2 has a bandgap of 2.7 eV and valence/conduction band positioning that make it ideal for water splitting. ZnS2, as well as other metastable phases, have yet to be synthesized in solution – let alone colloidally. This project will use solution-phase epitaxy and ion exchange on thermodynamically stable pyrite seeds to grow these metastable phases due to their intrinsically similar lattice planes. Pyrite and pyrite-type materials still contain many underexplored prospects that could be the subject of study for many years to come.

Research Area: Nanoscience
Mentor: Javier Vela

Investigation of Active Magnetocaloric Regenerators

Caloric materials change temperature in response to externally applied fields (magnetic, stress, electric) and are very promising for replacing conventional vapor-compression systems in cooling applications. Caloric refrigeration has the potential to improve efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of magnetocaloric technologies. One area that needs additional research is fabrication and manufacturing methods for active magnetic regenerators (AMR) made of magnetocaloric materials. In order to realize the potential of magnetic cooling, the active regenerator needs fine feature sizes for efficient heat transfer, low fluid-flow pressure losses, and efficient magnetization. The research project will focus on AMR designs and fabrication methods to achieve these goals and advance the overall state of the technology.

Research Area: Engineering Mechanical
Mentor: Julie Slaughter

Design, modeling and understanding of novel semiconductor nanostructures

The Ames Laboratory solid-state nuclear magnetic resonance (ss-NMR) project is engaged in the synthesis and characterization of novel nanostructures including two-dimensional semiconductors (borophanes, high-temperature stable MXenes), semiconductor quantum dots (including CdSe/CdS), and inorganic perovskite nanoparticles. Their properties depend critically on the surfaces of these nanostructures including surface functionalization, and NMR spectroscopy provides fascinating information on the local environments of atoms on the surface. This project will computationally model these nanostructures with density functional calculations, utilizing relativistic effects for heavy atoms, to determine the chemical shifts of atoms on surfaces and how these depend on the precise geometry and nanostructure. The project is expected to uncover novel atomistic models for nanostructures that can explain many puzzling features of ongoing experiments. This computational project can be performed remotely, and will be jointly performed with R. Biswas and A. Rossini at Ames Laboratory.
Research area: Nanoscience
Mentor: Rana Biswas

Mechanically Strengthened High Magnetic Performance Rare-earth Permanent Magnets

Rare-earth permanent magnets (REPMs) have excellent magnetic properties and have been widely used in energy conversion and storage, telecommunication, consumer electronics, biomedical devices, and magnetic sensors. However, REPMs are brittle and cannot be used for applications subjected to high stress, vibration, or mechanical shock. The brittleness also leads to magnet production loss up to 20-30% in volume and imposes limitations on part size and shape. This project is to produce REPMs (mainly Nd-Fe-B and Sm-Co sintered magnets) mechanically stronger than the commercial products while maintaining their excellent magnetic properties and reducing magnet waste rate to less than 10%. Especially, the new mechanical strengthening approaches and mechanisms will be studied by both experimental work and theoretical modeling. The novel mechanically strengthened high magnetic performance REPMs will be more cost-effective, efficient, and robust for energy-related applications while reducing the pressure on the critical material supply chain.
Research area: Materials Sciences
Mentor: Baozhi Cui

Exploring novel plasmonic phenomena in topological semimetals

Topological semimetals are a class of three-dimensional (3D) quantum materials with gapless electronic structures protected by both symmetry and topology. The most studied among all are the Dirac and Weyl semimetals, which are the three-dimensional (3D) analogs of graphene. While both semimetals share the linear Dirac dispersion close to the touching points of the valence and conduction bands (termed Dirac and Weyl points), the Weyl points always appear in pairs. More interestingly, the Weyl points of each pair have opposite chirality and act as the source/drain of the Berry curvature fields. Direct outcomes of the intriguing Weyl physics include the so-called chiral anomaly and the Fermi-arc surface states, which have been largely confirmed by experiments. The unique properties of Dirac and Weyl semimetals open up opportunities for breakthroughs in electronic, photonic, and quantum technologies. For example, it was predicted that surface plasmon polaritons (SPPs) formed due to the collective oscillations between photons and Weyl fermions could have hyperbolic and anisotropic dispersions, which enable the nonreciprocal flow of these plasmonic modes in real space. So far, studies of SPPs in topological semimetals are limited despite a lot of interest. Here we propose to perform systematic and comprehensive experimental and theoretical studies of SPPs in Dirac and Weyl semimetals. The major goal of the proposed research is to uncover the novel plasmonic properties of Dirac and Weyl semimetals and to achieve new plasmonic functionalities in devices based on topological semimetals.
Research area: Condensed Matter Physics
Mentor: Zhe Fei

Bacterial cell-cell communication in the rhizosphere

The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. We are interested in developing a deeper understanding of how plants interact with beneficial microbes in the rhizosphere. To establish a root-associated microbiome requires the ability of microbes to communicate with each other by chemical signals that they secrete. These include molecules referred to as quorum-sensing signals that can be either species-specific or universal languages. This project will explore the ability of a newly developed instrument for detecting these molecules produced by microbes. This devise relies on nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform to send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). We will develop a synthetic community that produces these signals or other metabolites that will be detected by the sensor. Through a “plug-and-play” synthetic microbial community we will also be able to introduce signal consumers and other microbes increase community complexity to assess how signal production influence fitness (growth and competitiveness), including identifying underlying mechanisms contributing to fitness.
Research area: Molecular Biology
Mentor: Larry Halverson

Complex layered pnictides

This project is devoted to development of novel pnictide materials with layered structure where electronic correlations are expected to be confined to metal-pnictogen layer, where metal is Cu, Ag, Au. Current SULI project is dedicated to analysis of crystal structure, transport properties (temperature and applied magnetic field dependences of electrical resistivity and heat capacity), and calculation of the electronic structure for pristine and aliovalent doped layered pnictides. The goal of the project is to outline correlations between transport properties and electron count/band structure of layered pnictides. Experimental work will be performed by graduate student researcher and data analysis can be completed remotely.
Research area: Quantum Materials
Mentor: Kirill Kovnir

Exploration of chiral chalcogenides

This project is devoted to development of novel complex chalcogenide materials. We have recently developed a new broad family of chiral and polar chalcogenide materials crystallizing in P63 space group. The phase space for this structure class includes over 2000 compounds. Current SULI project is dedicated to analysis of crystal structure, electronic structure, experimental bandgap, and non-linear optical properties data, with the aim to develop relationships between basic properties of constituent rare-earth and transition metals, and functional properties. Experimental work will be performed by postdoctoral researcher and data analysis can be completed remotely.
Research area: Inorganic Chemistry
Mentor: Kirill Kovnir

Defining the principles of aptamer-ligand interaction to improve aptamer affinity and specificity

Nucleic acid aptamers are proving to be extremely useful elements in sensors to detect identified targets such as proteins and small molecules. Obtaining aptamers starts with a pool of about 10^15 oligonucleotides that are selected by a repetitive process of 6-12 rounds of capture and amplification. The resulting oligonucleotide pool is then evaluated by informatics and likely aptamers are identified for further analysis. The best of these chosen aptamers are incorporated into sensors for detecting the target molecule. However, sensors must be both sensitive to the target molecule (analyte) and specific for that analyte over others. Although the selection protocol is effective in isolating aptamers with high affinity for the identified target, it has limited ability to select against alternate, potentially interfering molecules. Thus, it is important to understand how an aptamer interacts with its target and be able to predict interaction with interfering molecules or to change the structure/sequence of the aptamer to give it higher affinity or to make it more specific for its target molecule. To explore approaches to understanding aptamer-target interaction with the purpose of improving aptamer affinity and specificity, we are using a combined experimental and computational approach.
Research area: Biochemistry
Mentor: Marit Nilsen-Hamilton

Quantum Computing

As quantum information science (QIS) develops quantum computing architectures and storage, security approaches will be required to create trusted platforms and execution environments. QIS can be applied to near term utilization for security applications as well as evaluating future quantum architectures that would not be susceptible to classical computing vulnerabilities. This project aims to collect the current state of simulation/emulation environments including cloud services, cyber-security for quantum computing, and cyber-security utilizing quantum algorithms. This project would then create a framework for further quantum applications, document and create a development environment (e.g. python, QISKIT, etc.) and demonstrate a quantum algorithm for a cyber-security application such as random number or quantum key generation.
Research area: Materials Sciences
Mentor: Durga Paudyal

Machine Learning

The screening of novel materials with good performance and the modeling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modeling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.
Research area: Materials Sciences
Mentor: Durga Paudyal

Electronic structure

The rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements. Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.
Research area: Materials Sciences
Mentor: Durga Paudyal

Catalyst Development for Upgrading Renewable Feedstock

Lignin, as a renewable feedstock, is the only bio-derived source of aromatics in large abundance. The conversion of lignin has been achieved via catalytic reduction with transition metals (Pd, Pt, and Ru) as the catalyst. However, the implementation of the lignin utilization demands the use of less precious transition metals or full replacement with first-row transition metals. In this project, we will develop metal-based nanocatalyst for lignin conversion. A holistic design will be considered to preserve aromaticity and achieve high selectivity in cleaving ether linkages, including support, metal species, and dopants. Full characterization of the metal catalysts will be conducted such as powder XRD, and scanning transmission electron microscopy. The catalytic reactions will be carried out at elevated temperature and pressure (up to 240 °C and 50 bar).
Research area: Physical Chemistry
Mentor: Long Qi

Multifunctional Catalysts based on Zeolites

Zeolites are microporous crystalline materials composed of alumino-silicate or phosphate. Because of the high thermal stability and strong acidobascity, zeolites have been widely applied in refinery industry. Because regular pore morphologies of zeolites to control the diffusion and formation of molecules of different sizes, zeolites are often called molecular sieves. Besides, zeolites have also used as a support to accommodate molecular metal complexes or metal nanoparticles. The resulting materials become bifunctional, bearing both acidobascity of the zeolites and redox activity from the metals. We would like to apply zeolites as support for molecular organometallic complexes with rare earth metals and early transition metals, using a chemical liquid deposition method (CLD). The metal will bond directly with isolated bridging oxygen sites in the zeolite, resulting in a bifunctional catalyst. The catalyst can retain the microporous structure and enable hydro-treatment of both fossil and biomass resources. The hydrogenation activation and subsequent reactions will be studied with in situ spectroscopy including diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and operando high temperature/pressure solid-state NMR.
Research area: Physical Chemistry
Mentor: Long Qi

Investigation of Caloric Refrigeration Concepts

Caloric materials change temperature in response to externally applied fields (magnetic, stress, electric) and are very promising for replacing conventional vapor-compression systems in cooling applications. Caloric refrigeration has the potential to improve efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of magnetocaloric and elastocaloric technologies. One area that needs additional research is fabrication and manufacturing methods for active caloric regenerators (ACR) and new concepts for caloric heat pumping. The research project will focus on advancing caloric cooling technology and understanding the gaps and opportunities for research and development. Specific goals will be to understand caloric material behavior under different environmental conditions, develop models of material and device behavior, and validate through testing.
Research area: Engineering Mechanical
Mentor: Julie Slaughter

Programmable Assembly of Cubic Nanoparticles

Materials whose elementary components are nanoparticles (nanocrystals, colloids, etc., with
dimension between a few and one hundred nanometers) instead of atoms or molecules are a
new form of matter that has emerged over the last two decades. particular fascinating new type of nanocrystals, subject of much recent attention are metal halide perovskite semiconductors,
which are ionic compounds with the formula AMX3, where A and M are cations and X represents one or more halogen anions. They exhibit exceptional properties: high photoluminescence quantum yields and the ability to tune emission colors across the entire visible spectrum, with promising applications. Those nanocrystals have cubic shapes and recently have been shown to assemble in new types of complex superlattices. This project will determine by computational methods the different phases in which these cubic nanocrystals assemble.
Research area: Nanoscience
Mentor: Alex Travesset

Elucidating the Role of Hydrogen Bond Donor and Acceptor on Solvation in Deep Eutectic Solvents

Deep eutectic solvents (DESs) are homogenous mixtures formed through the combination of a hydrogen bond donor (HBD) and hydrogen bond acceptor (HBA). The physico-chemical properties of DESs (e.g., viscosity, hydrophobicity, melting point/glass transition temperature) can generally be modulated by tailoring the chemical structure and/or the relative molar ratio of HBA/HBD. To better predict the performance of DESs when they are used in chemical separations and catalysis, an understanding of their solvation interactions with dissolved molecules is essential. Until now, various empirical polarity scales based on solvatochromic probes have been used to characterize DESs. However, the polarity values measured by solvatochromic probes usually fall within a narrow range and do not adequately explain experimental observations when examining DESs with different chemical make-up. In this work, inverse chromatography will be used to characterize the solvation interactions of DESs containing a multitude of HBA and HBD combinations. Results from these studies will allow for various DES solvation interactions to be determined, including hydrogen bond acidity, hydrogen bond basicity, pi-pi and n-pi interactions, dispersion interactions, and dipolar/ion dipole interactions. The determined solvation characteristics will be used to develop a molecular model that describes the role DESs play in separations processes. This project will expose the SULI student to a wide range of different skills including: synthesis, purification, and characterization of DESs; chromatographic characterization; and computational modeling.
Research area: Analytical Chemistry
Mentor: Jared Anderson

Quantum computing algorithms for simulations of quantum materials

In this project, you will participate in our group's efforts to develop and apply quantum algorithms for simulating the behavior of quantum materials. Predicting the properties of real materials can guide experimental design efforts towards a wide variety of applications in energy and information sciences. This project focuses on the development and implementation of hybrid quantum-classical algorithms that can be run on state-of-the-art superconducting quantum processing units (QPU) of Rigetti Computing, Google and IBM. The goal of this project is to implement algorithms using the quantum computing language PyQuil and benchmark their performance on Rigetti QPUs using modern error mitigation protocols. The algorithms will be used to simulate the non-equilibrium dynamics of quantum materials, in particular, their nonlinear electromagnetic response in the presence of a strong coherent laser field.

Research area: Condensed Matter Physics

Mentor: Peter Orth

Deep learning approach to extracting crystal field parameters in quantum magnetic materials

This project will develop and apply modern deep machine learning algorithms based on convolutional neural networks to facilitate quantum materials research. In particular, the project goal is to extract crystal field (CF) parameters from thermodynamic data of rare-earth magnetic materials. We collaborate with an experimental group at Ames Laboratory that will provide the experimental data. The algorithm employs a two- dimensional convolutional neural network (CNN) that is trained on magnetization, magnetic susceptibility and specific heat data. This project is a continuation into a new direction of a successful project that was recently published here: https://arxiv.org/pdf/2011.12911.pdf. The goal is to implement Generative Adversarial Networks (GANs) and Reinforcement Learning (RL) algorithms to this problem.

Research area: Condensed Matter Physics
Mentor: Peter Orth

Quantum Computing

As quantum information science (QIS) develops quantum computing architectures and storage, security approaches will be required to create trusted platforms and execution environments. QIS can be applied to near term utilization for security applications as well as evaluating future quantum architectures that would not be susceptible to classical computing vulnerabilities. This project aims to collect the current state of simulation/emulation environments including cloud services, cyber-security for quantum computing, and cyber-security utilizing quantum algorithms. This project would then create a framework for further quantum applications, document and create a development environment (e.g. python, QISKIT, etc.) and demonstrate a quantum algorithm for a cyber-security application such as random number or quantum key generation.

Research area: Materials Science

Mentor: Durga Paudyal

Materials discovery and design using machine learning

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Materials Sciences
Mentor: Durga Paudyal

Chemical Upcycling of Waste Plastics

Polymers are irreplaceable in the global economy, with myriad uses in packaging, construction, transportation, electronics, and healthcare industries. However, their massive-scale manufacture, single-use function, long lifetimes, slow decomposition rates, and disruption of sensitive ecosystems have created a crisis of plastics waste. Unfortunately, conventional mechanical recycling methods are limited by considerable technological and economic challenges. Chemical upcycling, an emerging alternative to the classical recycling approach, would use plastic waste as a feedstock to synthesize value-added chemicals and materials. This project will focus on developing advanced catalysts that can achieve efficient and selective upcycling of waste plastics to high-value chemicals.

Research area: Renewable Energy Sciences and Technologies

Mentor: Wenyu Huang

Layered pnictides

This project is devoted to development of novel pnictide materials with layered structure where electronic correlations are expected to be confined to metal-pnictogen layer, where metal is Cu, Ag, Au. Current SULI project is dedicated to analysis of crystal structure, transport properties (temperature and applied magnetic field dependences of electrical resistivity and heat capacity), and calculation of the electronic structure for pristine and aliovalent doped layered pnictides. The goal of the project is to outline correlations between transport properties and electron count/band structure of layered pnictides. Experimental work will be performed by graduate student researcher and data analysis can be completed remotely.

Research area: Materials Sciences

Mentor: Kirill Kovnir

Novel complex chalcogenides

This project is devoted to development of novel complex chalcogenide materials. We have recently developed a new broad family of chiral and polar chalcogenide materials crystallizing in P63 space group. the phase space for this structure class includes over 2000 compounds. Current SULI project is dedicated to analysis of crystal structure, electronic structure, experimental bandgap, and non-linear optical properties data, with the aim to develop relationships between basic properties of constituent rare-earth and transition metals, and functional properties. Experimental work will be performed by postdoctoral researcher and data analysis can be completed remotely.

Research area: Materials Sciences
Mentor: Kirill Kovnir

Defining the principles of aptamer-ligand interaction to improve aptamer affinity and specificity

Sensitive biosensors are needed to detect biomolecules in the environment, soil and blood or tissue samples in order to monitor environmental contaminants, soil health or human disease. Nucleic acid aptamers are proving to be extremely useful elements in sensors to detect identified targets such as proteins and small molecules. Obtaining aptamers starts with a pool of about 10^15 oligonucleotides that are selected by a repetitive process of 6-12 rounds of capture and amplification. The resulting oligonucleotide pool is then evaluated by informatics and likely aptamers are identified for further analysis. The best of these chosen aptamers are incorporated into sensors for detecting the target molecule. However, the sensors must be both sensitive to the target molecule (analyte) and specific for that analyte over others. Although the selection protocol is effective in isolating aptamers with high affinity for the identified target, it has limited ability to select against alternate, potentially interfering molecules. Thus, it is important to understand how an aptamer interacts with its target and be able to predict interaction with interfering molecules or to change the structure/sequence of the aptamer to give it higher affinity or to make it more specific for its target molecule. To explore approaches to understanding aptamer-target interaction with the purpose of improving aptamer affinity and specificity, we are using a combined experimental and computational approach.

Research area: Biochemistry
Mentor: Marit Nilsen-Hamilton

Electronic structure of rare earth materials

The rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements. Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research area: Materials Sciences
Mentor: Durga Paudyal

Multifunctional Catalysts based on Single Site Catalyst

Zeolites are microporous crystalline materials composed of alumino-silicate or phosphate. Because of the high thermal stability and strong acidobascity, zeolites have been widely applied in refinery industry. Because regular pore morphologies of zeolites to control the diffusion and formation of molecules of different sizes, zeolites are often called molecular sieves. Besides, zeolites have also used as a support to accommodate molecular metal complexes or metal nanoparticles. The resulting materials become bifunctional, bearing both acidobascity of the zeolites and redox activity from the metals. We would like to apply zeolites as support for molecular organometallic complexes with rare earth metals and early transition metals, using a chemical liquid deposition method (CLD). The metal will bond directly with isolated bridging oxygen sites in the zeolite, resulting in a bifunctional catalyst. The catalyst can retain the microporous structure and enable hydro-treatment of both fossil and biomass resources. The hydrogenation activation and subsequent reactions will be studied with in situ spectroscopy including diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and operando high temperature/pressure solid-state NMR.

Research area: Physical Chemistry
Mentor: Long Qi

Quantitative analysis of structure and property relationship in quantum materials

Modern aberration-corrected transmission electron microscopy (TEM) and multifunctional detectors provide a platform to directly correlate materials atomic arrangement with their macroscopic properties. With growing data size and complexity, a computational-aided analysis is crucial to extract property-related structural information. This research project will focus on developing and implementing computer aided quantitative analysis methods for quantum materials. The student will be involved in developing codes for analyzing and interpreting of results for the Superconducting Quantum Materials and Systems Center (SQMS).

Research area: Engineering Materials
Mentor: Lin Zhou

Quantum computing algorithms for simulations of quantum materials

In this project, you will participate in our group's efforts to develop and apply quantum algorithms for simulating the behavior of quantum materials. Predicting the properties of real materials can guide experimental design efforts towards a wide variety of applications in energy and information sciences. This project focuses on the development and implementation of hybrid quantum-classical algorithms that can be run on state-of-the-art superconducting quantum processing units (QPU) of Rigetti Computing, Google and IBM. The goal of this project is to implement algorithms using the quantum computing language PyQuil and benchmark their performance on Rigetti QPUs using modern error mitigation protocols. The algorithms will be used to simulate the non-equilibrium dynamics of quantum materials, in particular, their nonlinear electromagnetic response in the presence of a strong coherent laser field.

Research area: Condensed Matter Physics

Mentor: Peter Orth

Deep learning approach to extracting crystal field parameters in quantum magnetic materials

This project will develop and apply modern deep machine learning algorithms based on convolutional neural networks to facilitate quantum materials research. In particular, the project goal is to extract crystal field (CF) parameters from thermodynamic data of rare-earth magnetic materials. We collaborate with an experimental group at Ames Laboratory that will provide the experimental data. The algorithm employs a two- dimensional convolutional neural network (CNN) that is trained on magnetization, magnetic susceptibility and specific heat data. This project is a continuation into a new direction of a successful project that was recently published here: https://arxiv.org/pdf/2011.12911.pdf. The goal is to implement Generative Adversarial Networks (GANs) and Reinforcement Learning (RL) algorithms to this problem.

Research area: Condensed Matter Physics
Mentor: Peter Orth

Quantum Computing

As quantum information science (QIS) develops quantum computing architectures and storage, security approaches will be required to create trusted platforms and execution environments. QIS can be applied to near term utilization for security applications as well as evaluating future quantum architectures that would not be susceptible to classical computing vulnerabilities. This project aims to collect the current state of simulation/emulation environments including cloud services, cyber-security for quantum computing, and cyber-security utilizing quantum algorithms. This project would then create a framework for further quantum applications, document and create a development environment (e.g. python, QISKIT, etc.) and demonstrate a quantum algorithm for a cyber-security application such as random number or quantum key generation.

Research area: Materials Science

Mentor: Durga Paudyal

Materials discovery and design using machine learning

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Materials Sciences
Mentor: Durga Paudyal

Elucidating the Role of Hydrogen Bond Donor and Acceptor on Solvation in Deep Eutectic Solvents

Deep eutectic solvents (DESs) are homogenous mixtures formed through the combination of a hydrogen bond donor (HBD) and hydrogen bond acceptor (HBA). The physico-chemical properties of DESs (e.g., viscosity, hydrophobicity, melting point/glass transition temperature) can generally be modulated by tailoring the chemical structure and/or the relative molar ratio of HBA/HBD. To better predict the performance of DESs when they are used in chemical separations and catalysis, an understanding of their solvation interactions with dissolved molecules is essential. Until now, various empirical polarity scales based on solvatochromic probes have been used to characterize DESs. However, the polarity values measured by solvatochromic probes usually fall within a narrow range and do not adequately explain experimental observations when examining DESs with different chemical make-up. In this work, inverse chromatography will be used to characterize the solvation interactions of DESs containing a multitude of HBA and HBD combinations. Results from these studies will allow for various DES solvation interactions to be determined, including hydrogen bond acidity, hydrogen bond basicity, pi-pi and n-pi interactions, dispersion interactions, and dipolar/ion dipole interactions. The determined solvation characteristics will be used to develop a molecular model that describes the role DESs play in separations processes. This project will expose the SULI student to a wide range of different skills including: synthesis, purification, and characterization of DESs; chromatographic characterization; and computational modeling.

Research area: Analytical Chemistry
Mentor: Jared Anderson

Synthesis and characterization of complex metal pnictides

Transition and rare-earth metal pnictides exhibit a diverse range of properties ranging from thermoelectric materials to high-temperature superconductors. Our research group work on synthesis, structural and properties characterization of novel complex pnictide materials containing transition and/or rare-earth metals. The project will include solid-state synthesis of novel compounds, determination of their crystal structure, and characterization of the electrical and heat transport properties.

Research area: Materials Sciences
Mentor: Kirill Kovnir

Catalytic Transformations of Biorenewables

The project is aimed to transform molecules derived from biorenewable sources into commodity chemicals. The student will learn to synthesize and characterize advanced catalysts to perform these transformations under mild conditions in an energy efficient manner. In addition to learn materials characterization techniques, the student will learn methods to monitor reaction progress and to identify target products. Methods may include X-ray diffraction, microscopy, surface physi- and chemisorption, UV/Vis, Infrared, fluorescence and/or NMR spectroscopy, and GC/MS.

Research area: Renewable Energy Sciences and Technologies
Mentor: Igor Slowing

Hybrid nanostructures for catalysis

Students will participate in a project aimed to prepare smart multifunctional nanodevices for catalyzing sequences of chemical reactions to convert biomass related products into biorenewable fuels and chemical commodities. The nanostructured materials will be composed of organic and inorganic species that will work cooperatively to effectively promote chemical conversions behaving like nanosized assembly lines. The students will be trained in the synthesis and characterization of hybrid mesoporous materials. They will use a series of analytical methods including powder x-ray diffraction, gas physi- and chemisorption and spectroscopy. Prior experience with any of the mentioned techniques is desirable, but not required, as training will be provided as needed.

Research area: Nanoscience
Mentor: Igor Slowing

Catalytic decontamination of water

The project is aimed at removing contaminants from waste water and turning them into useful products. The student will learn methods to produce, characterize and apply nanostructured catalytically active adsorbents. Techniques will include but will not be limited to x-ray diffraction, spectroscopies and chromatography.

Research area: Environmental Sciences
Mentor: Igor Slowing

Computational Methods for Assembly of Nanoparticles

We develop computational predictions of the assembly of nanoparticles into arrangements with long range order (=superlattices) by different methods strategies: hydrogen bonding, solving evaporation, and others. We develop methods for structure prediction and materials properties. We use statistical mechanics, molecular dynamics and machine learning. We are also interested in developing code. Knowledge in Python is highly desirable, but not necessary.

Research area: Nanoscience
Mentor: Alex Travesset

Bacterial cell-cell communication in the rhizosphere

The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. We are interested in developing a deeper understanding of how plants interact with beneficial microbes in the rhizosphere. To establish a root-associated microbiome requires the ability of microbes to communicate with each other by chemical signals that they secrete. These include molecules referred to as quorum-sensing signals that can be either species-specific or universal languages. This project will explore the ability of a newly developed instrument for detecting these molecules produced by microbes. This devise relies on nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform to send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). We will develop a synthetic community that produces these signals or other metabolites that will be detected by the sensor. Through a “plug-and-play” synthetic microbial community we will also be able to introduce signal consumers and other microbes increase community complexity to assess how signal production influence fitness (growth and competitiveness), including identifying underlying mechanisms contributing to fitness. The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. We are interested in developing a deeper understanding of how plants interact with beneficial microbes in the rhizosphere. To establish a root-associated microbiome requires the ability of microbes to communicate with each other by chemical signals that they secrete. These include molecules referred to as quorum-sensing signals that can be either species-specific or universal languages. This project will explore the ability of a newly developed instrument for detecting these molecules produced by microbes. This devise relies on nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform to send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). We will develop a synthetic community that produces these signals or other metabolites that will be detected by the sensor. Through a “plug-and-play” synthetic microbial community we will also be able to introduce signal consumers and other microbes increase community complexity to assess how signal production influence fitness (growth and competitiveness), including identifying underlying mechanisms contributing to fitness.

Research area: Molecular Biology
Mentor: Larry Halverson

Synthetic Microbial Communities for Exploring Plant-Microbe Interactions

We are interested in developing a deeper understanding of how plants interact with both beneficial and detrimental microbes in the rhizosphere. The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes but also with plants themselves. This project will build a testbed for a new instrument for detecting specific molecules produced by microbes or the plant in the rhizosphere. These nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform will send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). Our contribution is to develop a synthetic microbial community for assessing the efficacy of our imaging system while providing insight into the dynamics and fate of the targeted chemicals in the rhizosphere. We will develop synthetic biology tools for controlling production of targeted metabolites by one microbe and separate tools for detecting targeted metabolites by another. Through the construction of a “plug-and-play” synthetic community modelled on the natural maize rhizosphere microbiome, we will increase community complexity, including the introduction of natural producers and consumers of the targeted metabolites.

Research area: Molecular Biology
Mentor: Larry Halverson

Dynamic NMR Investigation of Supported Scandium Complexes

Single-site supported metal complexes are often seen as a bridge between homogeneous and heterogeneous catalysis fields. Their selectivity and activity can often be tuned by varying the structure of the ligands, in principle providing a path towards the purpose-driven design of catalysts, and their immobilization onto solid supports allows for the easy separation of the catalyst. Despite this little is known as to their precise atomic-level structures and even less is known about their structural dynamics. In this project we will use NMR spectroscopy to observe the dynamics of supported scandium complexes and determine how these are affected by structural features such as the steric bulk of the ligands, and the topology of the support. The undergraduate student working on this project will be tasked with the synthesis of isotopically-enriched scandium complexes and grafting them onto oxide supports for further analysis via NMR. This internship will provide experience in a synthetic organic and inorganic chemistry laboratory as well as in the use of state-of-the-art solid-state NMR spectroscopy.

Research area: Inorganic Chemistry
Mentor: Frederic Perras

Simulations of dilute magnetic structures

The student will use cluster computer to simulate magnetic properties of topological insulators (Tis) that are minutely doped with magnetic elements (Mn, Cr, Fe). The goal of the study is to determine the energy scale and the nature of the magnetic interactions of the doped elements in the TIs. Good computing skills using Matlab, Python (Anaconda, Jupyter), plotting routines are desired.

Research area: Condensed Matter Physics
Mentor: David Vaknin

Self-assembly and crystallization of nano-particles

We modify the surfaces of nano-particles by ligand exchange to promote specific interactions that can invoke self-assembly and crystallization of nano-particles into two- and three-dimensional crystals. The long-term goal is to produce so called meta-materials. We use various X-ray diffraction and spectroscopy techniques to determine the structures of the assemblies. The student will be involved in all facets of the project including analysis. Students with background in physics and chemistry with aspirations in materials science will benefit from our lab work. Basic knowledge of Python or any other language will be helpful

Research area: Nanoscience
Mentor: David Vaknin

Quantitative analysis of atomic columns in materials

Modern aberration-corrected transmission electron microscopy (TEM) and multifunctional detectors provide an unprecedented opportunity to study atom arrangement and chemistry in materials with sub angstrom resolution. With growing data size and complexity, a computational-aided analysis is crucial to extract property-related structural information. This research project will focus on developing and implementing computer-aided quantitative analysis methods for quantum materials. The student will be involved in developing codes for analyzing and interpreting results for the Superconducting Quantum Materials and Systems Center (SQMS). Knowledge of Python is required.

Research area: Condensed Matter Physics
Mentor: Lin Zhou

Investigation of Caloric Refrigeration Concepts

Caloric materials change temperature in response to externally applied fields (magnetic, stress, electric) and are very promising for replacing conventional vapor-compression systems in cooling applications. Caloric refrigeration has the potential to improve efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of caloric technologies for cooling. The research project will focus on demonstrating early-stage cooling concepts using magnetocaloric and elastocaloric materials.

Research area: Engineering Mechanical
Mentor: Julie Slaughter

Develop Dy-free Nd-Fe-B permanent magnets with high temperature stability

Rare earth (RE)-based Nd-Fe-B permanent magnets are used in most of these applications due to their high potential maximum energy product ((BH)max~59 MGOe) at room temperature. However, Nd-Fe-B magnets have poor thermal stability. A heavy rare earth element, Dy or Tb, has to be added to the magnets to enhance the coercivity and improve the thermal stability. The operating temperature of the magnets directly depends on the amount of Dy added. Unfortunately, Dy is expensive and scarce. It was considered as the #1 critical material by the U.S. Department of Energy in 2011 and remains critical today. The supply risks of Nd, Dy, and other RE has stimulated studies for Dy-lean or Dy-free Nd-Fe-B permanent magnets with sufficient energy density and thermal stability for high-performance electric motors and generators. This project is to develop Dy-free Nd-Fe-B magnets with high thermal stability by controlling the magnet's composition and microstructure.

Research area: Materials Sciences
Mentor: Wei Tang

Develop rare-earth free MnBi magnet for the radiation shielding of nuclear energy applications

Nuclear shielding is a growing market likely to become extremely important in the face of rising global interest in decarbonization. The ability to rapidly install and remove radiation shielding in the field enhances safety while simultaneously adding to worker efficiency. Current magnetic radiation shielding employs Nd-Fe-B (Nd2Fe14B) based magnets. However, they are largely limited to operational temperatures below ~150 °C and their performance drops rapidly above this temperature. MnBi is not as strong as Nd-Fe-B at room temperature, but it retains a greater fraction of its remanence to higher temperatures and remains viable as a permanent magnet to over 225 °C. There is a growing market for radiation shielding for use at higher temperatures.

Ames Lab will develop high-performance MnBi magnet and provide it to another DOE Lab (LLNL). MnBi will be combined with the LLNL’s innovative magnetic designs to develop new and portable radiation shielding.

Research area: Materials Sciences
Mentor: Wei Tang

Electronic structure of rare earth materials

The rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements. Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research area: Materials Sciences

Mentor: Durga Paudyal

Prediction of new materials and properties using machine learning (ML) approaches

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consumes tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Materials Sciences

Mentor: Durga Paudyal

Quantum Computing

As quantum information science (QIS) develops quantum computing architectures and storage, security approaches will be required to create trusted platforms and execution environments. QIS can be applied to near term utilization for security applications as well as evaluating future quantum architectures that would not be susceptible to classical computing vulnerabilities. This project aims to collect the current state of simulation/emulation environments including cloud services, cyber-security for quantum computing, and cyber-security utilizing quantum algorithms. This project would then create a framework for further quantum applications, document and create a development environment (e.g. python, QISKIT, etc.) and demonstrate a quantum algorithm for a cyber-security application such as random number or quantum key generation.

Research area: Materials Sciences

Mentor: Durga Paudyal

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable
energies and materials. However, both of them have their limitations. Precious metals
have low natural abundance and are expensive. Metal alloys have unstable surfaces
due to surface segregation under reaction conditions, which renders the identification of
active sites and the understanding of reaction mechanisms difficult. My research group
will address these limitations by developing new intermetallic NP catalysts. Intermetallic
compounds, which consist of two or more metallic elements, adopt
specific crystal structures as well as electronic structures different from the constituent
elements. The modified electronic structures of intermetallic compounds make them
unique catalytic materials. It has been proposed that such compounds should be treated
as new “elements”, considering their potential in catalysis. The inherent properties of
intermetallic compounds, stable and exhibit a large variety of structures, will help us to
discover catalysts with stable surfaces, consisting of more abundant metals, to replace
unstable alloy and precious metal catalysts.
Research area: Inorganic Chemistry
Mentor: Wenyu Huang

Developing Functionalized Graphene for Biomass Conversion

The goal of this research is to develop low-cost catalysts based on graphene-derived
nanomaterials and use them to improve the efficiency of several key steps in biomass
refinery. To make the cost of biomass-derived fuels comparable, or lower than that of
petroleum fuels, it is necessary to develop new catalysts and processes that can
substantially improve the efficiency of biomass refinery. Two attractive biomass refinery
processes, pyrolysis, and hydrolysis of lignocellulose, usually give molecules containing
high oxygen content, and thus low energy density to be used directly as fuel. Therefore,
upgrading of the lignocellulose derived oxygenates is necessary for them to be fit into
appropriate fuel classes (i.e., gasoline, diesel, or jet fuels). The general approaches for
upgrading the oxygenates are to decrease their oxygen contents, and to build carbon-
carbon bonds, targeting different fuel classes. Catalysts play a vital role in converting
and upgrading biomass to fuels, and thus need to be studied extensively. Catalysts
based on graphene-derived nanomaterials could greatly improve the efficiency of
biomass conversion and substantially decrease the cost of biomass conversion.

Research area: Renewable Energy Sciences and Technologies
Mentor: Wenyu Huang

Control heterogeneous catalysis at atomic and electronic-level using metal-organic
frameworks

To control heterogeneous catalysis at atomic and electronic-level represents one of the
most challenge research areas. Using metal-organic frameworks (MOFs) as hosts of
metal nanoclusters, we could reach an atomic and electronic-level control of
heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal
nanoclusters, have great potentials for catalysis due to their structural diversity,
flexibility, and tailorability, as well as high porosity. Compared to zeolite, the chemical
environment of each cage/cavity of MOFs can be controlled at the atomic-level by using
different organic linkers. The MOFs with isoreticular structures are particularly
interesting because they have exactly the same lattice structure, but different chemical
compositions. These different organic linkers or metal ion nodes of MOFs result in
geometrically identical cages of different chemical environments. Nanoclusters,
confined in these cages/cavities, would experience an atomic-level fine-tuned chemical
environment, and thus exhibit different activity and selectivity in heterogeneous
catalysis. During chemical conversion processes, reactants and reaction intermediates
could also sense these chemical environments that could alter their adsorption energy
and geometry, which will also affect the reaction activity and selectivity.
Research area: Nanoscience
Mentor: Wenyu Huang

Chiral Catalysis Using Surface-Engineered Heterogeneous Catalysts

Chirality, an essential attribute of nature, engenders unique pharmacological and
biological properties in a great variety of substances. However, the synthesis of chiral
molecules presents a unique challenge in catalysis. The potential to exhibit selectivity
beyond the standard structure is particularly challenging and requires a specifically
tuned catalyst to perform. This project will seek to perform this by modifying already
chemoselective heterogeneous catalysts by impregnating the support with chiral
modifiers. There are several potential heterogeneous catalysts to test, but an ideal case
would be one in which the chiral modifiers adsorb to a specific type of active site while
leaving another exposed. This would potentially force the reaction to produce only one

of the possible stereoisomers rather than a racemic mixture. Potential reactions for this
system include C=O hydrogenation for acetophenone or methyl pyruvate.
Research area: Physical Chemistry
Mentor: Wenyu Huang

Tuning Magnetic Ordering in Magnetic Materials Containing Rare Earths

The rare earths materials play an increasingly important role in modern technology. Among them, magnetic intermetallic alloys and compounds containing lanthanides are known for their both current (permanent magnets, magnetic actuators) and future (near room temperature magnetic cooling, quantum information) technologies. The proposed experimental research focuses on magnetic rare earth alloys, in particular on the optimization and control of their magnetic ordering. In our fundamental research we are exploring non-trivial approaches, such as, for example, enhancement of magnetic ordering temperature using chemical substitution of highly magnetic atoms (Gd, Tb, Dy) by non-magnetic atoms (e.g. Sc, Ti). We are looking for candidates interested in performing experimental synthesis (via melting and heat treatment) and basic characterization (X-ray powder diffraction and magnetic measurements) of ternary
and quaternary intermetallic compounds containing one or more rare earth element. The
anticipated outcome is a publication in a peer-reviewed science journal.
Research area: Materials Sciences
Mentor: Yaroslav Mudryk

Defining the principles of aptamer-ligand interaction to improve aptamer affinity and specificity

Nucleic acid aptamers are proving to be extremely useful elements in sensors to detect identified targets such as proteins and small molecules. Obtaining aptamers starts with a pool of about 10^15 oligonucleotides that are selected by a repetitive process of 6-12 rounds of capture and amplification. The resulting oligonucleotide pool is then evaluated by informatics and likely aptamers are identified for further analysis. The best of these chosen aptamers are incorporated into sensors for detecting the target molecule. However, sensors must be both sensitive to the target molecule (analyte) and specific for that analyte over others. Although the selection protocol is effective in isolating aptamers with high affinity for the identified target, it has limited ability to select against alternate, potentially interfering molecules. Thus, it is important to understand how an aptamer interacts with its target and be able to predict interaction with interfering molecules or to change the structure/sequence of the aptamer to give it higher affinity or to make it more specific for its target molecule. To explore approaches to understanding aptamer-target interaction with the purpose of improving aptamer affinity and specificity, we are using a combined experimental and computational approach.

Research area: Molecular Biology
Mentor: Marit Nilsen-Hamilton

Building an aptasensor to detect the SARS CoV-2 virus

In this period of COVID-19, it is essential that we develop fast and reliable tests for the virus that is causing this pandemic. This project is to build the parts of a new instrument for sensing specific molecules on viruses. The part we are focusing on first is to build the sensors that will be used to detect the virus particles. These sensors rely on aptamers to recognize the virus. Aptamers are nucleic acids that, like antibodies, specifically recognize a target protein or virus particle. However, unlike antibodies, aptamers can be selected in vitro and synthesized chemically. When aptamers are the means of detecting the virus the sensor is called an aptasensor. An aptasensor is being developed that will detect SARS CoV-2 virus particles and send signals to a central computer which converts the signal to a measure of the presence or absence of the virus. To build the sensors we will be using nucleic acid aptamers that specifically recognize the SARS CoV-2 virus. Compared with antibodies, aptamers have properties that are much more applicable to functioning on a range of sensor platforms. The aptamers will be integrated into a nanoporous anodized aluminum oxide sensing platform to create an aptasensor for detecting the virus presence. This aptasensor will be inexpensive and not require refrigeration and thus could be stored for long periods before it is used. It will also be easy to use and so can be used in remote areas of the country outside of hospital laboratories.

Research area: Engineering Biological (nonmedical)
Mentor: Marit Nilsen-Hamilton

Quantum computing algorithms for simulations of quantum materials

In this SULI, you will participate in our group's efforts to develop and apply quantum algorithms for simulating the behavior of quantum materials. Predicting the properties of real materials can guide experimental design efforts towards a wide variety of applications in energy and information sciences. As part of a national Department of Energy quantum center "Superconducting Quantum Materials and Systems" (SQMS), this project focuses on the development and implementation of hybrid quantum-classical algorithms that can be run on state-of-the-art superconducting quantum processing units (QPU) of our SQMS partner Rigetti Computing. The goal of this project is to implement algorithms using the quantum computing language PyQuil and benchmark their performance on Rigetti QPUs using modern error mitigation protocols. The algorithms will be used to simulate the non-equilibrium dynamics of quantum materials, in particular, their nonlinear electromagnetic response in the presence of a strong coherent laser field.

Research area: Condensed Matter Physics
Mentor: Peter Orth

Exploring gate-tunable polariton transport in 2D semiconductors

Exciton polaritons are quasiparticles generated due to the coherent coupling between photons and excitons in semiconductors. The strong light-matter interactions and the bosonic nature of exciton polaritons have led to many groundbreaking discoveries such as Bose-Einstein condensation, polariton superfluidity, and polariton lasing. In recent years, exciton polaritons were studied extensively in group VI transition-metal dichalcogenides (TMDs) with chemical formula MX2 (M = Mo, W; X = S, Se) – a class of van der Waals two-dimensional (2D) semiconductors. It was found that exciton polaritons in this class of materials are stable at ambient conditions and cover a wide spectral range from near-infrared to visible frequencies can be tailored by controlling the sample thickness with atomic accuracy. Nevertheless, gate tunability of exciton polariton transport, which is essential for the realization of tunable polaritonic devices (e.g., polariton transistors and polariton modulators) in future nanophotonic circuits, has not been realized yet.

In this project, we propose to explore gate-tunable polariton transport in TMDs by using the state-of-the-art scattering-type scanning near-field optical microscopy (s-SNOM). The objectives of this research are: (1) to fabricate gate-tunable TMD devices; (2) to image the propagative polaritons with s-SNOM; (3) to realize practical polariton devices. The proposed research will deepen our understanding of the nano-optical and nano-electronic physics of these 2D semiconductors, revolutionize our approach towards tunable nanophotonics in the technologically important near-infrared to visible regions, and establish TMD atomic layers as novel materials that are promising for coherent nanophotonic applications in optical communications and data processing with broad bandwidth and active controllability.

Research area: Atomic, Molecular, and Optical Sciences
Mentor: Zhe Fei

Modeling of self-assembly and reaction-diffusion processes far-from-equilibrium

Physical and chemical processes occurring far-from-equilibrium can exhibit an extraordinarily rich variety of spatio-temporal behavior (development of complex morphologies for self-assembly of nanoscale materials, non-linear kinetics or dynamics, wave propagation and pattern formation in reaction-diffusion systems). This behavior is the result of the cooperative interaction between large numbers of atoms or molecules. We attempt to model this behavior at the atomistic level. Conventional Molecular Dynamics simulations (just integrating Newton's equations) cannot describe the behavior of interest on the relevant time scales. Thus, we instead use 'stochastic models' just tracking atom positions, and implementing various relevant processes or moves with probabilities which reflect the physical rates for such processes (e.g., adsorption, desorption, diffusion, and reaction for processes occurring at surfaces). The models are analyzed by Kinetic Monte Caro simulation, but also by analytical mathematical methods. Familiarity with Mathematica or Matlab, and ideally with coding in other languages, is particularly valuable.

Research area: Nanoscience
Mentor: Jim Evans

Exploration of Complex Metal Pnictides Containing Refractory Metalloids, Carbon and Boron

The project will investigate ternary and quaternary intermetallics containing tetrels (Si, Ge, Sn) or refractory metalloid (B, C) and pnictogen (P, As, Sb, Bi) or chalcogen (S, Se, Te). A novel synthetic approach will be developed by binding metals and metalloids in one compounds and than reacting it with volatile pnictogen. Novel phases will be synthesized with unique crystal structures due to flexibility provided by the presence of two non-metal elements able to form strong covalent bonds. Presence of transition and rare-earth metal will provide local magnetic moments and strong spin-orbit coupling which will result in exciting magnetic and transport properties. Properties tunability will be the main focus to realize quantum materials based on the proposed objects of study. Using computational input, the stability of such quaternary phases for second and third row transition metals, as well as systems contaning boron and carbon will be investigated. The mechanism of the synthesis will also be explored.

Research area: Materials Sciences
Mentor: Georgiy Akopov

4DMAPS: Portable sensors for monitoring rhizosphere

Project will address the challenge of monitoring the physiology and inteactions of plants with other organisms in soil and their responses to the chemical and microbial composition of the rhizosphere. We will develop a network of aptamer functionalized sensors to monitor the chemicals excreted by plant roots and their interactions with surrounding soil. The students will design, fabricate and characterize sensors that will be used in the soil monitoring.
Nanoporous alumina membranes have become a ubiquitous biosensing platform for a
variety of applications and aptamers are being increasingly utilized as recognition elements in protein sensing devices. Combining the advantages of the two, we will utilize the aptamer functionalized alumina membranes for label-free sensitive detection of small molecules using a four-electrode electrochemical cell. An arduino based reader will be developed to monitor the impedance of the alumina membrane in the four electrode cell configuration.
Research area: Engineering Mechanical
Mentor: Pranav Shrotriya

Optical and Microscopy Characterizations of Transmon Quantum Bits

A grand challenge underlying quantum information science (QIS) applications is how to characterize microstructures of transmon qubits and increase coherence time. Pushing the state-of-art requires visionary experiments and versatile tools, particularly, at space-time limit of deep-subwavelength (<100 nm) scales and microwave/terahertz frequencies. The project aims to apply various microscopy and nano-photonics tools to study transmon quantum bits at the space-time limit. The dynamic and coherent processes to be demonstrated include conductivity imaging, tunneling junction characterizations, supercurrent control.

These align well to four Priority Research Opportunities (PROs) identified in the BES report “Opportunities for Basic Research for Next-Generation Quantum Systems”. Our research involves quantum control and sensing directly targeting quantum information functionality, and probing and understanding of foundational phenomena using optics and micorospcy methods. Our success will provide unprecedented quantum control and imaging capabilities “never-before-accessible” for communities of condensed matter/materials, photonics and quantum control/information science.

This work was supported by the Ames Laboratory, the US Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division under contract No. DEAC02- 07CH11358, and by Superconducting Quantum Materials and Systems Center, an National QIS Center funded by the U.S. DOE, Office of Basic Energy Sciences.

Research area: Condensed Matter Physics
Mentor: Jigang Wang

Quantitative visualization of atom movement in materials

Modern transmission electron microscopy (TEM) and multifunctional detectors provide an unprecedented opportunity to study the phase transition process at the atomic scale in materials under external stimuli, such as temperature, magnetic field, and stress. With growing data size and complexity in multidimensionality, a computational-aided analysis is crucial to extract structural evolution information. This research project will focus on developing image-based quantitative analysis methods from TEM images of various materials, including magnetic materials, metals, and ceramics. The student will be involved in developing codes for analyzing and interpreting results. The knowledge of Python is required.

Research area: Materials Sciences
Mentor: Lin Zhou

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements”, considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Research area: Nanoscience
Mentor: Wenyu Huang

Control heterogeneous catalysis at atomic and electronic-level using metal-organic frameworks

To control heterogeneous catalysis at atomic and electronic-level represents one of the most challenge research areas. Using metal-organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal nanoclusters, have great potentials for catalysis due to their structural diversity, flexibility, and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at the atomic-level by using different organic linkers. The MOFs with isoreticular structures are particularly interesting because they have exactly the same lattice structure, but different chemical compositions. These different organic linkers or metal ion nodes of MOFs result in geometrically identical cages of different chemical environments. Nanoclusters, confined in these cages/cavities, would experience an atomic-level fine-tuned chemical environment, and thus exhibit different activity and selectivity in heterogeneous catalysis. During chemical conversion processes, reactants and reaction intermediates could also sense these chemical environments that could alter their adsorption energy and geometry, which will also affect the reaction activity and selectivity.

Research area: Inorganic Chemistry
Mentor: Wenyu Huang

Prediction of new materials and properties using machine learning (ML) approaches

Prediction of new materials and properties using machine learning (ML) approaches
The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Materials Sciences
Mentor: Durga Paudyal

Electronic structure of rare earth materials

The rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements. Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research Area: Materials Sciences
Mentor: Durga Paudyal

Synthesis and characterization of complex metal pnictides

Pnictides exhibit a diverse range of properties ranging from thermoelectric materials to high-temperature superconductors. Our research group work on synthesis, structural and properties characterization of novel complex pnictide materials containing transition and/or rare-earth metals. The project will include solid-state synthesis of novel compounds, determination of their crystal structure, and characterization of the electrical and heat transport properties.

Research area: Materials Sciences
Mentor: Kirill Kovnir

Investigation of Caloric Refrigeration Concepts

Caloric materials change temperature in response to externally applied fields (magnetic,
stress, electric) and are very promising for replacing conventional vapor-compression
systems in cooling applications. Caloric refrigeration has the potential to improve
efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of caloric
technologies for cooling. The research project will focus on demonstrating early-stage
cooling concepts using magnetocaloric and elastocaloric materials.
Research area: Engineering Mechanical
Mentor: Julie Slaughter

Self assembly and crystallization of nano-particles

We modify the surfaces of nano-particles by ligand exchange to promote specific interactions that can invoke self assembly and crystallization of nano-particles into two- and three-dimensional crystals. The long term goal is to produce so called meta-materials. We use various X-ray diffraction and spectroscopy techniques to determine the structures of the assemblies. The student will be involved in all facets of the project including analysis. Students with background in physics and chemistry with aspirations in materials science will benefit from our lab work. Basic knowledge of Python or any other language will be helpful.

Research area: Nanoscience
Mentor: David Vaknin

Catalytic Conversion of Carbon Dioxide

Carbon Capture, Utilization and Storage is a highly-sought goal by Department of Energy. We would like to target the catalytic conversion of carbon dioxide to produce value-added oxygenates as advanced fuels and chemicals.

Highly selective catalysts will be synthesized with first-row transition metals. The metal-based nanoparticles will be supported on an acid-resistant and water-tolerant porous catalyst. A plug-flow reactor will be designed and custom-made, which should be readily scalable. The reactor will be coupled with the fully-automated chromatographic techniques for online analysis. Hydrogen gas will be used as the reducing agents. Reactions of CO2 with epoxides will be studied as well for the production of organic carbonates. In both cases, reaction conditions, including flow rate, temperature, system pressure, etc., will be investigated to evaluate the selectivities of various catalysts in a continuous flow mode.

Research area: Physical Chemistry
Mentor: Long Qi

Data Science for Catalysis

Data science has drastically changed how data are collected and analyzed. We would like to introduce new methodologies in data science into catalysis science, which is the key in petroleum refinery and pharmaceutical industries.

In this project, new methods including simulation and modeling, and machine learning will be developed and implemented to increase the instrument efficiency and understand more of the experimental data.

Research area: Physical Chemistry
Mentor: Long Qi

Defining the principles of aptamer-ligand interaction to improve aptamer affinity and specificity

Nucleic acid aptamers are proving to be extremely useful elements in sensors to detect identified targets such as proteins and small molecules. Obtaining aptamers starts with a pool of about 1015oligonucleotides that are selected by a repetitive process of 6-12 rounds of capture and amplification. The resulting oligonucleotide pool is then evaluated by informatics and likely aptamers are identified for further analysis. The best of these chosen aptamers are incorporated into sensors for detecting the target molecule. However, sensors must be both sensitive to the target molecule (analyte) and specific for that analyte over others. Although the selection protocol is effective in isolating aptamers with high affinity for the identified target, it has limited ability to select against alternate, potentially interfering molecules. Thus, it is important to understand how an aptamer interacts with its target and be able to predict interaction with interfering molecules or to change the structure/sequence of the aptamer to give it higher affinity or to make it more specific for its target molecule. To explore approaches to understanding aptamer-target interaction with the purpose of improving aptamer affinity and specificity, we are using a combined experimental and computational approach.

Research area: Molecular Biology
Mentor: Marit Nilsen-Hamilton

Bacterial cell-cell and bacterial-plant interactions in the rhizosphere

The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes but also with plants themselves. Many of these molecules can stimulate or inhibit bacterial or even plant growth. To establish a root-associated microbiome requires the ability of microbes to communicate with each other by chemical signals that they secrete. This project will explore the ability of a newly developed instrument for detecting these molecules produced by microbes. This devise relies on nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform to send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). We will develop a synthetic community that produces these signals or other metabolites that will be detected by the sensor. Through a “plug-and-play” synthetic microbial community we will also be able to introduce signal consumers and assess how signal production influence fitness (growth and competitiveness), including identifying underlying mechanisms contributing to fitness.

Research area: Engineering Biological (nonmedical)
Mentor: Larry Halverson

Plastic Upcycling Through Chemical Catalysis

We are developing catalysts for conversion of polymers, the principle component in plastics, from waste materials into new polymers, monomers for repolymerization (recycling), or new valuable chemicals. The vision is that such chemical transformations will provide incentives for collection and processing of plastic waste, which currently are landfilled or discarded one hundred megaton scale. Our approach involves synthesis of supported catalysts and investigation of reactions that break the carbon-carbon bonds polymer chain backbones.

Research area: Inorganic Chemistry

Mentor: Aaron Sadow

Quantitative visualization of atomic columns in materials

Modern aberration-corrected transmission electron microscopy (TEM) and multifunctional detectors provide an unprecedented opportunity to study atom arrangement and chemistry in materials with sub angstrom resolution. With growing data size and complexity, a computational-aided analysis is crucial to extract property-related structural information. This research project will focus on developing atomic-scale image-based quantitative analysis methods for various material systems, including topological magnetic materials and ferroelectric oxides. The student will be involved in developing codes for analyzing and interpreting of results. The knowledge of Python or similar programing language is required.

Which of the following Research Areas is best aligned with this proposed project?

Research area: Materials Sciences
Mentor: Lin Zhou

Chiral Catalysis Using Specially Heterogeneous Catalysts

Chirality, an essential attribute of nature, engenders unique pharmacological and biological properties in a great variety of substances. However, the synthesis of chiral molecules presents a unique challenge in catalysis. The potential to exhibit selectivity beyond the standard structure is particularly challenging and requires a specifically tuned catalyst to perform. This project will seek to perform this by modifying already chemoselective heterogeneous catalysts by impregnating the support with chiral modifiers. There are several potential heterogeneous catalysts to test, but an ideal case would be one in which the chiral modifiers adsorb to a specific type of active site while leaving another exposed. This would potentially force the reaction to produce only one of the possible stereoisomers rather than a racemic mixture. Potential reactions for this system include C=O hydrogenation for acetophenone or methyl pyruvate.

Research area: Nanoscience
Mentor: Wenyu Huang

Heterogeneous Rare-earth Permanent Magnets with Enhanced Mechanical Properties

Rare-earth permanent magnets (REPMs) have excellent magnetic properties and have been widely used in energy conversion and storage, telecommunication, consumer electronics, biomedical devices, and magnetic sensors. However, REPMs are brittle and cannot be used for applications subjected to high stress, vibration or mechanical shock. The brittleness also leads to the magnet production loss up to 20-30% in volume and imposes limitations on part size and shape. This project is to produce REPMs (mainly Sm-Co and Nd-Fe-B sintered magnets) mechanically and magnetically stronger than the commercial products while reducing magnet waste rate to less than 10%. The novel magnets will be more cost-effective, efficient and robust for energy-related applications while reducing the pressure on critical material supply chain.

Research area: Materials Science
Mentor: Baozhi Cui

High Performance Permanent Magnets for Energy Applications

Permanent magnets are increasingly ubiquitous in many applications but are reliant upon expensive rare earth elements which must be obtained from foreign sources. The high cost of expensive rare earth elements is already a threat to technological advancement. Disruption in the supply of these rare earth elements will hinder progress in high-tech and clean energy technologies including wind energy, magnetic resonance imaging, data storage, electric vehicles and many more. As a result, there are global technological and energy security needs to make permanent magnets with reduced or without rare earth elements. This research will enable students to gain hands-on experience on making powerful permanent magnets. Students will be exposed to our state of the art research equipment for production and testing of magnetic properties. The proposed project will focus mainly on making magnets with reduced or no critical rare earth elements. The student will use our new Controlled Atmosphere Materials Processing System for the research.As part of the Critical Materials Institute, students will have the opportunity to observe a multi-institutional research project designed to strategically support the competitiveness of the United States in clean energy technologies.

Research area: Materials Science
Mentor: Ikenna Nlebedim

Synthetic Microbiomes for Exploring Plant-Microbe Interactions

We are interested in developing a deeper understanding of how plants interact with both beneficial and detrimental microbes in the rhizosphere. The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes but also with plants themselves. This project will build a test-bed for a new instrument for detecting specific molecules produced by microbes or the plant in the rhizosphere. These nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform will send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). Our contribution is to develop a synthetic microbial community for assessing the efficacy of our imaging system while providing insight into the dynamics and fate of the targeted chemicals in the rhizosphere. We will develop synthetic biology tools for controlling production of targeted metabolites by one microbe and separate tools for detecting targeted metabolites by another. Through the construction of a “plug-and-play” synthetic community modeled on the natural maize rhizosphere microbiome, we will increase community complexity, including the introduction of natural producers and consumers of the targeted metabolites.

Research area: Engineering Biological (nonmedical)
Mentor: Larry Halverson

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements” considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Research area: Materials Sciences
Mentor: Wenyu Huang

Control heterogeneous catalysis at atomic and electronic-level using metal-organic frameworks

To control heterogeneous catalysis at atomic and electronic-level represents one of the most challenge research areas. Using metal organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal nanoclusters, have great potentials for catalysis due to their structural diversity, flexibility and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at atomic-level by using different organic linkers. The MOFs with isoreticular structures are particularly interesting because they have exactly the same lattice structure, but different chemical compositions. These different organic linkers or metal ion nodes of MOFs results geometrically identical cages of different chemical environments. Nanoclusters, confined in these cages/cavities, would experience an atomic-level fine-tuned chemical environment, and thus exhibit different activity and selectivity in heterogeneous catalysis. During chemical conversion processes, reactants and reaction intermediates could also sense these chemical environments that could alter their adsorption energy and geometry, which will also affect the reaction activity and selectivity.

Research area: Nanoscience
Mentor: Wenyu Huang

Plant/microbe communication with aptamers

The rhizosphere is a thin layer around the roots of a plant where microbes congregate. Some microbes are beneficial and others pathogenic. Plants need microbes in the rhizosphere for their proper nutrition. So, they do things to attract the beneficial microbes. For example, up top 70% of a plant's energy can be excreted through the roots into the surrounding rhizosphere to feed the microbes, some of which convert nitrogen gas into forms like ammonium that can be absorbed by the plant. We are interested in understanding this mutualistic relationship as it occurs in the soil. We are also interested in understanding how plants interact with harmful microbes that sometimes enter the rhizosphere. To gain this understanding, we need to obtain data on the molecular signals by which plants and microbes interact. This project is to build the parts of a new instrument for sensing specific molecules in the rhizosphere. The part we are focusing on first is to build the sensors that will be used to detect the molecules. These sensors will send signals to a central computer which will create a 3D image of the distribution of this chemical around the root over time (4D). To build the sensors we will be selecting and maturing nucleic acid aptamers that specifically recognize the molecules of interest. Similar in their function to antibodies, aptamers have properties that are much more applicable to functioning underground than do antibodies. Once selected and matured, the aptamers will be integrated into a nanoporous anodized aluminum oxide sensing platform to create a sensor that will be placed at the tips of the instrument to be placed in the soil for molecular recognition.

Research area: Engineering Biological (nonmedical)
Mentor: Marit Nilsen-Hamilton

Design of Physically Motivated Anisotropic Atomic Orbital Basis Sets

The goal of theoretical chemistry is to explain and predict chemical phenomena. Physically we know that such phenomena are described by the Schrödinger equation (SE); unfortunately, analytic solutions to the SE do not exist for most chemical systems of interest. Nonetheless, it is possible to approximate the SE, to arbitrary accuracy, starting from the familiar linear combination of atomic orbitals (AO) ansatz. The AOs in this ansatz are numeric approximations to the familiar s, p, d, f, etc. orbitals introduced in general chemistry. Such AOs are well suited for describing an isolated atom, but poorly describe the anisotropic electronic environments found around atoms in molecular environments. The goal of this project is to extend the traditional AO basis sets so that the resulting basis sets includes anisotropy. The resulting anisotropic AOs (AAO) are the numeric analogs of the traditional sp, sp2, sp3, ... hybrid AOs. Because AAOs better describe the anisotropic electronic environments within molecules, It is anticipated that AAO ansätze for molecular systems will be shorter compared to traditional, similar quality, AO ansätze. Given that the time to approximate the SE scales non-linearly with respect to the number of AOs, this means that AAOs should reduce the time needed to approximate the SE. Resultantly, AAOs have the potential to extend the domain of chemical systems to which theoretical chemistry is applicable.

Research area: Theoretical Chemistry
Mentor: Richard Ryan

Synthesis and characterization of novel pnictide materials

Pnictides exhibit a diverse range of properties ranging from thermoelectric materials to high-temperature superconductors. Our research group work on synthesis, structural and properties characterization of novel complex pnictide materials containing transition and/or rare-earth metals. The project will include solid-state synthesis of novel compounds, determination of their crystal structure, and characterization of the electrical and heat transport properties.

Research area: Materials Sciences
Mentor: Kirill Kovnir

Prediction of new materials and properties using machine learning (ML) approaches

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Engineering Materials
Mentor: Durga Paudyal

Multifunctional Catalysts based on Zeolites

Zeolites are microporous crystalline materials composed of alumino-silicate or phosphate. Because of the high thermal stability and strong acidobascity, zeolites have been widely applied in refinery industry. Because regular pore morphologies of zeolites to control the diffusion and formation of molecules of different sizes, zeolites are often called molecular sieves. Besides, zeolites have also used as a support to accommodate molecular metal complexes or metal nanoparticles. The resulting materials become bifunctional, bearing both acidobascity of the zeolites and redox activity from the metals.

We would like to apply zeolites as support for molecular organometallic complexes with rare earth metals and early transition metals, using a chemical liquid deposition method (CLD). The metal will bond directly with isolated bridging oxygen sites in the zeolite, resulting in a bifunctional catalyst. The catalyst can retain the microporous structure and enable hydro-treatment of both fossil and biomass resources. The hydrogenation activation and subsequent reactions will be studied with in situspectroscopy including diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and operando high temperature/pressure solid-state NMR.

Research Area: Materials Sciences
Mentor: Long Qi

Development of Quantum Sensors for Quantum Materials Research

Quantum materials such as superconductors and magnetic skyrmions show promise for advanced technologies including energy-efficient electronics, and technologies based on quantum information science (QIS). Realization of such advanced technologies depend on how well we understand fundamental physics of the relevant quantum material. This requires novel methods of sensing and characterization with better sensitivity and minimal effect on the studied system. In other words, quantum materials need quantum methods of sensing.

Here at Ames Laboratory, we develop new techniques to study magnetic and electronic properties of quantum materials. One of them is based on the nitrogen-vacancy (NV) atomic defect in diamond. This “NV-center” can be viewed as an electron “trapped” in diamond crystal and we access quantum energy levels of electron spin to detect the presence of very weak magnetic fields.

The SULI student will learn the techniques of quantum sensing and atomic force microscopy (AFM) and develop multi-disciplinary hands-on skills working with optical, electronic, and microwave networks. Essentially, the student will learn how condensed matter physicist works in the lab, starting from the development and improvement of the experiment, acquisition of scientific data, and to writing research reports potentially resulting in peer-reviewed journals.

Research area: Condensed Matter Physics
Mentor: Naufer Nusran

Exploration of Complex Metal Pnictides Containing refractory Metalloids, Boron and Carbon

The project will investigate ternary and quaternary intermetallics containing refractory metalloid (B, C) and pnictogen (P, As, Sb, Bi). A novel synthetic approach will be developed by binding metals and metalloids in one compounds and than reacting it with volatile pnictogen. Novel phases will be synthesized with unique crystal structures due to flexibility provided by the presence of two non-metal elements able to form strong covalent bonds. Presence of transition and rare-earth metal will provide local magnetic moments and strong spin-orbit coupling which will result in exciting magnetic and transport properties. Properties tunability will be the main focus to realize quantum materials based on the proposed objects of study. Using computational input, the stability of such quaternary phases for second and third row transition metals, as well as systems contaning boron and carbon will be investigated. The mechanism of the synthesis will also be explored.

Research Area: Materials Sciences
Mentor: Georgiy Akopov

Catalyst Development for Upgrading Renewable Feedstock

Lignin, as a renewable feedstock, is the only bio-derived source of aromatics in large abundance. The conversion of lignin has been achieved via catalytic reduction with transition metals (Pd, Pt, and Ru) as the catalyst. However, the implementation of the lignin utilization demands the use of less precious transition metals or full replacement with first-row transition metals.

In this project, we will develop metal-based nanocatalyst for lignin conversion. A holistic design will be considered to preserve aromaticity and achieve high selectivity in cleaving ether linkages, including support, metal species, and dopants. Full characterization of the metal catalysts will be conducted such as powder XRD, and scanning transmission electron microscopy. The catalytic reactions will be carried out at elevated temperature and pressure (up to 240 °C and 50 bar).

Research Area: Engineering Chemical
Mentor: Long Qi

Benchmarking quantum chemistry methods on advanced computers

This project is part of the GAMESS exascale computing project (ECP). GAMESS is an electronic structure theory suite of programs that has about 150,000 users. The project will involve benchmarking and profiling several core features of GAMESS on the most advanced computers in the DOE system.

Research Area: Computational Sciences
Mentor: Mark Gordon

Developing Functionalized Graphene for Biomass Conversion

The goal of this research is to develop low cost catalysts based on graphene-derived nanomaterials, and use them to improve the efficiency of several key steps in biomass refinery. To make the cost of biomass derived fuels comparable, or lower than that of petroleum fuels, it is necessary to develop new catalysts and processes that can substantially improve the efficiency of biomass refinery. Two attractive biomass refinery processes, pyrolysis and hydrolysis of lignocellulose, usually give molecules containing high oxygen content, and thus low energy density to be used directly as fuel. Therefore, upgrading of the lignocellulose derived oxygenates is necessary for them to be fit in appropriated fuel classes (i.e., gasoline, diesel, or jet fuels). The general approaches for upgrading the oxygenates are to decrease their oxygen contents, and to build carbon-carbon bonds, targeting different fuel classes. Catalysts play a vital role in converting and upgrading biomass to fuels, and thus need to be studied extensively. Catalysts based on graphene-derived nanomaterials could greatly improve the efficiency of biomass conversion and substantially decrease the cost of biomass conversion.

Research Area: Renewable Energy Sciences and Technologies
Mentor: Wenyu Huang

Plastic Upcycling Through Chemical Catalysis

We are developing catalysts for conversion of polymers, the principle component in plastics, from waste materials into new polymers, monomers for repolymerization (recycling), or new valuable chemicals. The vision is that such chemical transformations will provide incentives for collection and processing of plastic waste, which currently are landfilled or discarded on hundred megaton scale. Our approach involves synthesis of supported catalysts and investigation of reactions that break the carbon-carbon bonds polymer chain backbones.

Research Area: Inorganic Chemistry
Mentor: Aaron Sadow

4DMAPS: Portable sensors for monitoring the rhizosphere

Project will address the challenge of monitoring the physiology and inteactions of plants with other organisms in soil and their responses to the chemical and microbial composition of the rhizosphere. We will develop a network of aptamer functionalized sensors to monitor the chemicals excreted by plant roots and their interactions with surrounding soil. The students will design, fabricate and characterize sensors that will be used in the soil monitoring. Nanoporous alumina membranes have become a ubiquitous biosensing platform for a variety of applications and aptamers are being increasingly utilized as recognition elements in protein sensing devices. Combining the advantages of the two, we will utilize the aptamer functionalized alumina membranes for label-free sensitive detection of small molecules using a four-electrode electrochemical cell. An arduino based reader will be developed to monitor the impedance of the alumina membrane in the four electrode cell configuration.

Research area: Engineering Mechanical
Mentor: Pranav Shortriya

3D Printing Nanostructures

Over the last couple of decades, scientists have been able to develop a tremendous control over the synthesis and properties of materials at the nanoscale. New, emergent behaviors have been discovered upon investigation of nanostructures. A significant challenge nowadays is how to preserve and extend these nanoparticle behaviors to larger scales, specifically to the macroscale, the world we humans are the most familiar with. To reach this goal we need to create a bridge between the nano and the macro scales, this bridge is known as the mesoscale. We are currently learning and developing tools to orderly assemble nanostructures at the mesoscale, i.e. ordering nanometer sized particles along micron-sized domains. The missing link is putting together micron-sized arrays into millimeter or centimeter sized shapes, and we believe this can be accomplished by 3D printing technologies. In this project, the students will develop inks made up of nanostructured materials so that they can be printed into three dimensional objects that can be as large as a human hand and demonstrate the capacity to organize matter at the nano-, meso- and macro-scales.

Research area: Nanoscience

Mentor: Igor Slowing

Hybrid nanostructures for catalysis

Students will participate in a project aimed to prepare smart multifunctional nanodevices for catalyzing sequences of chemical reactions to convert biomass related products into biorenewable fuels and chemical commodities. The nanostructured materials will be composed of organic and inorganic species that will work cooperatively to effectively promote chemical conversions behaving like nanosized assembly lines. The students will be trained in the synthesis and characterization of hybrid mesoporous materials. They will use a series of analytical methods including powder x-ray diffraction, gas physi- and chemisorption and spectroscopy. Prior experience with any of the mentioned techniques is desirable, but not required, as training will be provided as needed.

Research area: Nanoscience
Mentor: Igor Slowing

Assembly of Nanoparticles at Solid Surfaces

This project will investigate how to assemble nanostructures at solid interfaces. The nanostructures consist of ordered arrays of nanoparticles capped with hydrocarbon ligands. Following our previously developed methods, we will compute the potential of mean force and free energy of the assembled structures and investigate the ligand textures, with the emergence of ligand vortices, as predicted by the Orbifold Topological Model (OTM), which will be generalized to include interfaces also. The results will be incorporated in our HOODLT software. Although knowledge of Python is not a requisite, willingness to learn it is.

Research Area: Nanoscience
Mentor: Alex Travesset

Topological Changes of Electronic Structure during Symmetry-Breaking Structural Transformations in Quantum Systems

While scientifically intriguing, changes of the electronic structure during a lattice transformation offer a means to control aspects of quantum materials for practical applications. In this summer project the student will explore electron-lattice coupling in a model system and how it alters properties. An educational scaffolding and guidance will be provided by the experts in classical and quantum lattice Monte Carlo methods.

The determinant Quantum Monte Carlo (DQMC) method has been widely applied to investigate magnetic, pairing, and charge correlations of interacting electron Hamiltonians, like the Hubbard model. Prior investigations have focussed on the square lattice geometry, because of its relevance to physics of the cuprate superconductors, and, more recently, to honeycomb lattices which host Dirac fermions. In this project we propose the DQMC investigation of the Hubbard model on a lattice that interpolates between these geometries. In other words, we will study the electronic structure during a lattice transformation.

The student will begin by performing simulations of the classical Ising model on such an interpolating lattice to gain familiarity with Monte Carlo methods. The student will also learn how to compute tight-binding energy bands for an understanding of the Hubbard model in the noninteracting limit. The student will adapt an existing DQMC code to the interpolating geometry and run the simulations. The tight-binding computation will serve as a useful check of the modified code.

The outcome will be a better understanding of the electron-lattice coupling in a selected class of quantum materials, especially under non-hydrostatic stress during a lattice transformation involving strongly correlated electrons.

Research area: Condensed Matter Physics
Mentor: Nikolai Zarkevich

CMakePP: Facilitating Software Interoperability from the Build System Up

There is significant momentum in computational chemistry to develop a software ecosystem populated with independent, reusable libraries. In theory, these libraries can be easily adopted by any of the various computational chemistry packages, thereby avoiding the metaphorical "reinventing of the wheel." In practice this is a tall order requiring library developers to design for all contact points between their library and the existing software package. Usually the developers of the libraries have given extensive consideration to the application programming interface (API), but particularly for compiled libraries, typically little consideration has been afforded to ensuring that the library also integrates with the existing software package's build system. While this may seem like a trivial consideration, the reality is that the build systems for most existing software packages are extremely complex, tightly coupled, and fragile. Consequentially leveraging these reusable libraries often requires significant effort on the software package side. Making matters worse this additional effort is often hidden from the community because build systems are often an afterthought. The proposed research seeks to develop CMakePP, an extension to the popular CMake build system, which will make adding additional libraries as effortless as possible. The power of CMakePP will be demonstrated by case studies focusing on integrating some of the more popular reusable libraries with the software package NWChemEx

Research Area: Theoretical Chemistry
Mentor: Ryan Richard

Investigation of Caloric Refrigeration Concepts

Caloric materials change temperature in response to externally applied fields (magnetic, stress, electric) and are very promising for replacing conventional vapor-compression systems in cooling applications. Caloric refrigeration has the potential to improve efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of caloric technologies for cooling. The research project will focus on demonstrating early-stage cooling concepts using magnetocaloric and elastocaloric materials.

Research Area: Engineering Mechanical
Mentor: Julie Slaughter

Characterization of Energy Materials by Solid-State NMR Spectroscopy

The properties, activity, and performance of many energy relevant materials are governed by the structure of their surface, subsurface and interfacial regions. For example, the efficiency of solid-state lighting and photo-voltaic (PV) devices based upon semiconductor nanoparticles (NPs) is controlled by the surface termination and the distribution of elements within the NPs . The lack of techniques for atomic-level structural characterization often makes it difficult to test even the basic hypotheses relating materials’ structure to performance and hindering their rational design. In this project, students will develop and apply solid-state NMR spectroscopy to determine the atomic level structure of complex and disordered energy materials such as nanoparticles. This will be accomplished by using the state-of-the-art 263 GHz/400 MHz DNP NMR system hosted in the Ames lab. With DNP and other NMR techniques we can obtain order of magnitude improvements in sensitivity which allow us to characterize dilute sites on the surfaces of nanomaterials.

Research area: Physical Chemistry
Mentor: Aaron Rossini

Self assembly and crystallization of nano-particles

We modify the surfaces of nano-particles by ligand exchange to promote specific interactions that can invoke self assembly and crystallization of nano-particles into two- and three-dimensional crystals. The long term goal is to produce so called meta-materials. We use various X-ray diffraction and spectroscopy techniques to determine the structures of the assemblies. The student will be involved in all facets of the project including analysis. Students with background in physics and chemistry with aspirations in materials science will benefit from our lab work. Basic knowledge of Python or any other language will be helpful.

Research area: Materials Sciences
Mentor: David Vaknin

Tuning Magnetic Ordering in Magnetic Materials Containing Rare Earths

The rare earths materials play an increasingly important role in modern technology. Among them, magnetic intermetallic alloys and compounds containing lanthanides are known for their both current (permanent magnets, magnetic actuators) and future (near room temperature magnetic cooling, quantum information) technological applications. The proposed experimental research focuses on magnetic rare earth alloys, in particular on the tuning and control of their magnetic ordering. In our fundamental research we are exploring non-trivial approaches, such as, for example, enhancement of magnetic ordering temperature using chemical substitution of highly magnetic atoms (Gd, Tb, Dy) by non-magnetic atoms (e.g. Sc, Ti). We are looking for candidates interested in performing experimental synthesis (via melting and heat treatment) and basic characterization (X-ray powder diffraction and magnetic measurements) of ternary and quaternary intermetallic compounds containing one or more rare earth element. The anticipated outcome is a publication in a peer-reviewed science journal.

Research area: Materials Sciences
Mentor: Yaroslav Mudryk

Effect of controlled order superconductors using high precision magnetic susceptometer

When a LC circuit is combined with a special semiconductor diode, named a ''tunneling diode'', which has a negative resistance region due to the effect of quantum mechanical tunneling, one can make a high resolution resonator (fundamental frequency of about 14 MHz) with a noise level of 0.05 Hz - one part per billions resolution. This so-called tunnel diode resonator (TDR) technique has been used to probe magnetic property of various magnets and superconductors. In our laboratory, we developed high stability resonator and use it to measure high precision magnetic susceptibility. The student that participates in SULI program will build a hands-on TDR resonator and study the unconventional superconductors which have multiple superconducting gaps under extreme conditions (low-temperature, high-magnetic field, and high-pressure). During this project, the student will learn how condensed matter experimentalists work in the lab from developing tools to acquiring scientific results to writing a research article. Indeed, some of previous SULI students participated in several articles as a coauthor. For more information, please visit our group website.

Research area: Condensed Matter Physics
Mentor: Kyuil Cho

Data Science for Catalysis

Data science has drastically changed how data are collected and analyzed. We would like to introduce new methodologies in data science into catalysis science, which is the key in petroleum refinery and pharmaceutical industries.

In this project, new methods including simulation and modeling, and machine learning will be developed and implemented to increase the instrument efficiency and understand more of the experimental data.

Research area: Physical Chemistry
Mentor: Long Qi

Catalytic Transformations of Biorenewables

The project is aimed to transform molecules derived from biorenewable sources into commodity chemicals. The student will learn to synthesize and characterize advanced catalysts to perform these transformations under mild conditions in an energy efficient manner. In addition to learn materials characterization techniques, the student will learn methods to monitor reaction progress and to identify target products. Methods may include X-ray diffraction, microscopy, surface physi- and chimisorption, UV/Vis, Infrared, fluorescence and/or NMR spectroscopy, and GC/MS.

Research area: Organic Chemistry
Mentor: Igor Slowing

Security Frameworks for Quantum Computing

As quantum information science (QIS) develops quantum computing architectures and storage, security approaches will be required to create trusted platforms and execution environments. QIS can be applied to near term utilization for security applications as well as evaluating future quantum architectures that would not be susceptible to classical computing vulnerabilities. This project aims to collect the current state of simulation/emulation environments including cloud services, cyber-security for quantum computing, and cyber-security utilizing quantum algorithms. This project would then create a framework for further quantum applications, document and create a development environment (e.g. python, Q#, etc.) and demonstrate a quantum algorithm for a cyber-security application such as random number or quantum key generation.

Research area: Engineering Materials
Mentor: Durga Paudyal

Development of room temperature ferromagnetic nanoparticles for biomedical applications

In collaboration with Virginia Commonwealth University, Ames Laboratory, US Department of Energy, in conducting research on development of new forms of magnetic nanoparticles that show ferromagnetic transition (with high magnetic moment) at or close to room temperature. These nanoparticles have many biomedical applications including MRI contrast agents. These particles can reduce the static magnetic field needed in MRI thus reducing the size and cost of the MRI equipment significantly. This project will involve preparation of these magnetic nanoparticles and characterization. A patent based on the scalable synthesis of fine particles of one of rare-earth based metal based compound has been granted to the PI and his collaborators. Students working on this topic will have opportunity to get acquainted with the art and science of synthesis of inorganic/hybrid materials and perform cutting edge characterization experiments. If results mandate, the student will be able to publish their work or submit new patents based on several possible new applications of this material.

Research area: Materials Sciences
Mentor: Shalabh Gupta

Application of 3D Printing Additive Manufacturing Techniques to Lithium-ion Batteries

The project proposes to implement fused filament 3D printing for prototyping high capacity lithium-ion battery (~50-70% of commercial). An experimental protocol will be developed considering combination of different electrolyte, binder, electrochemically active and magnetic-filler materials to produce pliable electrode filaments. Increasing the loading fraction of active electrode material in the filament will be targeted, thus improving the electrochemical capacity. The project proposes to implement magnetic field while printing of magnetically active electrode filaments to align the pores in the inactive material, thus reducing the tortuosity of the printed sample. Electrochemical testing of the printed electrodes will be performed against lithium metal as reference, and also for a full cell to characterize the performance of the cell. Mathematical analysis will be performed to model a 1-D lithium battery and incorporate the impact of pore alignment of the electrochemical transport properties.

The student will be involved in developing several combinations of active material, binder and magnetic filler composites to achieve filaments with highest loading fraction of active material. The student will aid in 3-D printing of the dry electrode and perform electrochemical characterization on the assembled cell. The cell will be assembled, and electrolyte will be prepared by mentor. The student will learn and aid in development of mathematical model for battery simulations.

Research area: Materials Sciences
Mentor: Ikenna Nlebedim

High Performance Permanent Magnets for Energy Applications

Permanent magnets are increasingly ubiquitous in many applications but are reliant upon expensive rare earth elements which must be obtained from foreign sources. The high cost of expensive rare earth elements is already a threat to technological advancement. Disruption in the supply of these rare earth elements will hinder progress in high-tech and clean energy technologies including wind energy, magnetic resonance imaging, data storage, electric vehicles and many more. As a result, there are global technological and energy security needs to make permanent magnets with reduced or without rare earth elements.

This research will enable students to gain hands-on experience on making powerful permanent magnets. Students will be exposed to our state of the art research equipment for production and testing of magnetic properties. The proposed project will focus mainly on making magnets with reduced or no critical rare earth elements. The student will use our new Controlled Atmosphere Materials Processing System for the research.

As part of the Critical Materials Institute, students will have the opportunity to observe a multi-institutional research project designed to strategically support the competitiveness of the United States in clean energy technologies.

Research area: Materials Sciences
Mentor: Ikenna Nlebedim

Assembly of nanoparticles by tuning external conditions

This proposal aims at developing the theoretical physics and chemistry of a form of matter that has been emerging during the past twenty years, has already presented with new and exciting fundamental problems and that is now at the point where it may lead to major technological breakthroughs: materials whose elementary components are nanoparticles (nanocrystals, colloids, etc. with dimension between a few and one hundred nanometers) instead of atoms or molecules. The workshop will bring together physicists, chemists and material scientists, both theorists and experimentalists, in an effort to advance the fundamental science of this very young eld. The problems and questions that will be addressed are: Towards programmable matter: Can we control the dynamical scales involved in assembly? What properties or structures can be realized that are not possible in traditional materials of atoms or molecules?

For that purpose, we will use state of the art computational tools to predict the assembly of different nanocrystals in superstructures.

Research area: Materials Sciences
Mentor: Alex Travesset

Rare-earth permanent magnets

Rare-earth permanent magnets (REPMs) have excellent magnetic properties and have been widely used in energy conversion and storage, telecommunication, consumer electronics, biomedical devices, and magnetic sensors. However, REPMs are brittle and cannot be used for applications subjected to high stress, vibration or mechanical shock. The brittleness also leads to the magnet production loss up to 20-30% in volume and imposes limitations on part size and shape. This project is to produce REPMs (mainly Sm-Co and Nd-Fe-B sintered magnets) mechanically and magnetically stronger than the commercial products while reducing magnet waste rate to less than 10%. The novel magnets will be more cost-effective, efficient and robust for energy-related applications while reducing the pressure on critical material supply chain.

Research area: Materials Sciences
Mentor: Baozhi Cui

Quantitative visualization of atomic columns in materials

Modern aberration-corrected transmission electron microscopy (TEM) and multifunctional detectors provide an unprecedented opportunity to study atom arrangement and chemistry in materials with sub angstrom resolution. With growing data size and complexity, a computational-aided analysis is crucial to extract property-related structural information. This research project will focus on developing atomic-scale image-based quantitative analysis methods for various material systems, including topological magnetic materials and ferroelectric oxides. The student will be involved in developing codes for analyzing and interpreting of results. The knowledge of Python or similar programing language is required.

Research area: Materials Sciences
Mentor: Lin Zhou

Tracking dynamics of magnetic topological particles

Magnetic skyrmions are nanoscale vortex-like swirling spin objects that have attracted considerable interest as information carriers for future spintronic devices. Lorentz transmission electron microscopy (LTEM) allows us to observe skyrmions directly in real-space. As atoms in real-crystal, the skyrmion arrangement plays an important role in their formation. This research project will study the kinetics of skyrmion using in-situ LTEM. The student will be involved in developing computational-aided methods for LTEM image analysis. The knowledge of Python or similar programing language is required.

Research area: Condensed Matter Physics
Mentor: Lin Zhou

Nano-plasmonic studies of graphene-based van der Waals systems

Surface plasmon polaritons are collective oscillations of charges on the surface of metals or semiconductors. These surface modes are in vogue for their ability to confine and control electromagnetic waves at length scales much shorter than the diffraction limit. The search for agile plasmonic media is a vibrant research field with promising technological applications. Graphene offers a number of desirable plasmonic characteristics including high confinement, long lifetime, broad spectral range and electrical tunability. These unique properties make graphene a good candidate for plasmonic applications in the technologically-important infrared regime that is not accessible by conventional plasmonics based on noble metals. Despite all the above merits, the plasmonic properties and functionalities of single-layer graphene alone are still limited. One convenient way to engineer graphene plasmons is by constructing van der Waals (vdW) coupled systems based on graphene and/or other layered materials. Indeed, the two-dimensional (2D) nature of graphene makes it extremely sensitive to interlayer coupling that could dramatically modify the properties of Dirac fermions and their plasmonic excitations. In this project, the undergraduate student will work with graduate students to explore novel plasmonic properties and functionalities through systematic nano-infrared studies of various types of graphene-based vdW systems. The objectives of this research are (1) to design and fabricate graphene-based vdW systems by accurately controlling the stacking order, (2) to excite, probe, and characterize plasmons in these vdW structures with the advanced near-field nanoscope, (3) to extract essential parameters of the observed plasmons through rigorous modeling of the experimental data, (4) to achieve active control and manipulations of these plasmons by electrical gating and optical pumping.

Research area: Condensed Matter Physics
Fei Zhe

Quantum information science- modeling the control of qubits

Quantum information science (QIS) is one of the fastest evolving fields of science and technology, that holds enormous potential for quantum computing, communication and information storage. QIS has promise for solving computational problems that can not be presently accomplished. While the classical bit exists in 2 states 0 and 1, the basic element in QIS is the qubit – represented by a local spin vector. Since the spin vector can point in any direction, potentially far greater information can be stored in a qubit than a classical bit.

A very attractive solid-state qubit that we are studying consists of a rare earth (RE) ion in an insulating host crystal. The RE ion has a spin moment that can be addressed and controlled.

In this project we will model the behavior of these qubits in nanocavities that enhance the intensity of light in the cavity, and enhance the interaction of light with the qubit. We will simulate how the state if the qubit can be changed with external photons.

Research area: Condensed Matter Physics
Mentor: Rana Biswas

Growth and characterization of novel intermetallic compounds

The SULI student will learn the fundamentals of single crystal growth of new materials, primarily using high temperature solution growth. Depending on the interests of the student and current efforts in the group systems with superconducting, magnetic, structural, and/or electronic transitions will be studied. The SULI student will also become familiar with measurements of thermodynamic (magnetization) and transport (resistivity) properties.

Research area: Condensed Matter Physics
Mentor: Paul Canfield

Computational Studies of Heterogeneous Catalysis

Ames Laboratory scientists have synthesized and characterized various mesoporous silica nanoparticles (MSN) which have proven to be excellent heterogeneous catalysts. We will perform quantum chemistry calculations to study the mechanisms for reactions such as the nitroaldol reaction in MSN.

Research area: Theoretical Chemistry
Mentor: Mark Gordon

Assembly of Magnetic Two-Dimensional Materials

Two dimensional (2D) magnetic materials are promising materials for next-generation of spintronic devices due to appealing properties, such as high flexibility, optical transparency, and high electron mobility, of layered van der Waals materials when exfoliated to the monolayer limit. For spintronic applications, the major challenges are to enhance Curie temperature, perpendicular magnetic anisotropy (PMA), and sensitivity of PMA to the electric field. These properties can be tuned by doping, interfacing with metal layers, elastic strain, or by controlling stacking and relative in-plane orientation of the atomic planes. These factors comprise a complex parameter space in optimizing these properties. Our strategy is to combine material synthesis, high-resolution transmission electron microscope experiments, and the predictive power of ab initio calculations to control the structure and tailor the functional properties of the 2D magnetic materials. Systems of interest include VI3, CrI3, Fe3GeTe2, and Cr2Ge2Te6. The work will provide insight into the structure-properties relationship in these materials and potentially lay a foundation for a broader scope of research. Students will collaborate with local experimentalists.

Research area: Materials Sciences
Mentor: Liqin Ke

Electronic structure of rare earth materials

The rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements. Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research area: Engineering Materials
Mentor: Durga Paudyal

Synthetic Microbiomes for Exploring Plant-Microbe Interactions

We are interested in developing a deeper understanding of how plants interact with both beneficial and detrimental microbes in the rhizosphere. The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes but also with plants themselves. This project will build a test-bed for a new instrument for detecting specific molecules produced by microbes or the plant in the rhizosphere. These nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform will send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). Our contribution is to develop a synthetic microbial community for assessing the efficacy of our imaging system while providing insight into the dynamics and fate of the targeted chemicals in the rhizosphere. We will develop synthetic biology tools for controlling production of targeted metabolites by one microbe and separate tools for detecting targeted metabolites by another. Through the construction of a “plug-and-play” synthetic community modeled on the natural maize rhizosphere microbiome, we will increase community complexity, including the introduction of natural producers and consumers of the targeted metabolites.

Research area: Engineering Biological (nonmedical)
Mentor: Larry Halverson

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements” considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Research area: Materials Sciences
Mentor: Wenyu Huang

Control heterogeneous catalysis at atomic and electronic-level using metal-organic frameworks

To control heterogeneous catalysis at atomic and electronic-level represents one of the most challenge research areas. Using metal organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal nanoclusters, have great potentials for catalysis due to their structural diversity, flexibility and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at atomic-level by using different organic linkers. The MOFs with isoreticular structures are particularly interesting because they have exactly the same lattice structure, but different chemical compositions. These different organic linkers or metal ion nodes of MOFs results geometrically identical cages of different chemical environments. Nanoclusters, confined in these cages/cavities, would experience an atomic-level fine-tuned chemical environment, and thus exhibit different activity and selectivity in heterogeneous catalysis. During chemical conversion processes, reactants and reaction intermediates could also sense these chemical environments that could alter their adsorption energy and geometry, which will also affect the reaction activity and selectivity.

Research area: Nanoscience
Mentor: Wenyu Huang

Plant/microbe communication with aptamers

The rhizosphere is a thin layer around the roots of a plant where microbes congregate. Some microbes are beneficial and others pathogenic. Plants need microbes in the rhizosphere for their proper nutrition. So, they do things to attract the beneficial microbes. For example, up top 70% of a plant's energy can be excreted through the roots into the surrounding rhizosphere to feed the microbes, some of which convert nitrogen gas into forms like ammonium that can be absorbed by the plant. We are interested in understanding this mutualistic relationship as it occurs in the soil. We are also interested in understanding how plants interact with harmful microbes that sometimes enter the rhizosphere. To gain this understanding, we need to obtain data on the molecular signals by which plants and microbes interact. This project is to build the parts of a new instrument for sensing specific molecules in the rhizosphere. The part we are focusing on first is to build the sensors that will be used to detect the molecules. These sensors will send signals to a central computer which will create a 3D image of the distribution of this chemical around the root over time (4D). To build the sensors we will be selecting and maturing nucleic acid aptamers that specifically recognize the molecules of interest. Similar in their function to antibodies, aptamers have properties that are much more applicable to functioning underground than do antibodies. Once selected and matured, the aptamers will be integrated into a nanoporous anodized aluminum oxide sensing platform to create a sensor that will be placed at the tips of the instrument to be placed in the soil for molecular recognition.

Research area: Engineering Biological (nonmedical)
Mentor: Marit Nilsen-Hamilton

Design of Physically Motivated Anisotropic Atomic Orbital Basis Sets

The goal of theoretical chemistry is to explain and predict chemical phenomena. Physically we know that such phenomena are described by the Schrödinger equation (SE); unfortunately, analytic solutions to the SE do not exist for most chemical systems of interest. Nonetheless, it is possible to approximate the SE, to arbitrary accuracy, starting from the familiar linear combination of atomic orbitals (AO) ansatz. The AOs in this ansatz are numeric approximations to the familiar s, p, d, f, etc. orbitals introduced in general chemistry. Such AOs are well suited for describing an isolated atom, but poorly describe the anisotropic electronic environments found around atoms in molecular environments. The goal of this project is to extend the traditional AO basis sets so that the resulting basis sets includes anisotropy. The resulting anisotropic AOs (AAO) are the numeric analogs of the traditional sp, sp2, sp3, ... hybrid AOs. Because AAOs better describe the anisotropic electronic environments within molecules, It is anticipated that AAO ansätze for molecular systems will be shorter compared to traditional, similar quality, AO ansätze. Given that the time to approximate the SE scales non-linearly with respect to the number of AOs, this means that AAOs should reduce the time needed to approximate the SE. Resultantly, AAOs have the potential to extend the domain of chemical systems to which theoretical chemistry is applicable.

Research area: Theoretical Chemistry
Mentor: Richard Ryan

Synthesis and characterization of novel pnictide materials

Pnictides exhibit a diverse range of properties ranging from thermoelectric materials to high-temperature superconductors. Our research group work on synthesis, structural and properties characterization of novel complex pnictide materials containing transition and/or rare-earth metals. The project will include solid-state synthesis of novel compounds, determination of their crystal structure, and characterization of the electrical and heat transport properties.

Resarch area: Materials Sciences
Mentor: Kirill Kovnir

Prediction of new materials and properties using machine learning (ML) approaches

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Engineering Materials
Mentor: Durga Paudyal

Multifunctional Catalysts based on Zeolites

Zeolites are microporous crystalline materials composed of alumino-silicate or phosphate. Because of the high thermal stability and strong acidobascity, zeolites have been widely applied in refinery industry. Because regular pore morphologies of zeolites to control the diffusion and formation of molecules of different sizes, zeolites are often called molecular sieves. Besides, zeolites have also used as a support to accommodate molecular metal complexes or metal nanoparticles. The resulting materials become bifunctional, bearing both acidobascity of the zeolites and redox activity from the metals.

We would like to apply zeolites as support for molecular organometallic complexes with rare earth metals and early transition metals, using a chemical liquid deposition method (CLD). The metal will bond directly with isolated bridging oxygen sites in the zeolite, resulting in a bifunctional catalyst. The catalyst can retain the microporous structure and enable hydro-treatment of both fossil and biomass resources. The hydrogenation activation and subsequent reactions will be studied with in situspectroscopy including diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and operando high temperature/pressure solid-state NMR.

Research Area: Materials Sciences
Mentor: Long Qi

Development of Quantum Sensors for Quantum Materials Research

Quantum materials such as superconductors and magnetic skyrmions show promise for advanced technologies including energy-efficient electronics, and technologies based on quantum information science (QIS). Realization of such advanced technologies depend on how well we understand fundamental physics of the relevant quantum material. This requires novel methods of sensing and characterization with better sensitivity and minimal effect on the studied system. In other words, quantum materials need quantum methods of sensing.

Here at Ames Laboratory, we develop new techniques to study magnetic and electronic properties of quantum materials. One of them is based on the nitrogen-vacancy (NV) atomic defect in diamond. This “NV-center” can be viewed as an electron “trapped” in diamond crystal and we access quantum energy levels of electron spin to detect the presence of very weak magnetic fields.

The SULI student will learn the techniques of quantum sensing and atomic force microscopy (AFM) and develop multi-disciplinary hands-on skills working with optical, electronic, and microwave networks. Essentially, the student will learn how condensed matter physicist works in the lab, starting from the development and improvement of the experiment, acquisition of scientific data, and to writing research reports potentially resulting in peer-reviewed journals.

Research area: Condensed Matter Physics
Mentor: Naufer Nusran

Exploration of Complex Metal Pnictides Containing refractory Metalloids, Boron and Carbon

The project will investigate ternary and quaternary intermetallics containing refractory metalloid (B, C) and pnictogen (P, As, Sb, Bi). A novel synthetic approach will be developed by binding metals and metalloids in one compounds and than reacting it with volatile pnictogen. Novel phases will be synthesized with unique crystal structures due to flexibility provided by the presence of two non-metal elements able to form strong covalent bonds. Presence of transition and rare-earth metal will provide local magnetic moments and strong spin-orbit coupling which will result in exciting magnetic and transport properties. Properties tunability will be the main focus to realize quantum materials based on the proposed objects of study. Using computational input, the stability of such quaternary phases for second and third row transition metals, as well as systems contaning boron and carbon will be investigated. The mechanism of the synthesis will also be explored.

Research Area: Materials Sciences
Mentor: Georgiy Akopov

Imaging and Exploiting Nanoscale Heterogeneities

Our research focuses on using imaging methods to discover and to exploit nanoscale heterogeneity in various systems. Laser-based detection systems and sophisticated data analysis are employed in the process. Our work is highly collaborative and involves other DOE-funded researchers.

Research Area: Analytical Chemistry
Mentor: Jacob Petrich

Catalyst Development for Upgrading Renewable Feedstock

Lignin, as a renewable feedstock, is the only bio-derived source of aromatics in large abundance. The conversion of lignin has been achieved via catalytic reduction with transition metals (Pd, Pt, and Ru) as the catalyst. However, the implementation of the lignin utilization demands the use of less precious transition metals or full replacement with first-row transition metals.

In this project, we will develop metal-based nanocatalyst for lignin conversion. A holistic design will be considered to preserve aromaticity and achieve high selectivity in cleaving ether linkages, including support, metal species, and dopants. Full characterization of the metal catalysts will be conducted such as powder XRD, and scanning transmission electron microscopy. The catalytic reactions will be carried out at elevated temperature and pressure (up to 240 °C and 50 bar).

Research Area: Engineering Chemical
Mentor: Long Qi

3D Printing Nanostrutures

Over the last couple of decades, scientists have been able to develop a tremendous control over the synthesis and properties of materials at the nanoscale. New, emergent behaviors have been discovered upon investigation of nanostructures. A significant challenge nowadays is how to preserve and extend these nanoparticle behaviors to larger scales, specifically to the macroscale, the world we humans are the most familiar with. To reach this goal we need to create a bridge between the nano and the macro scales, this bridge is known as the mesoscale. We are currently learning and developing tools to orderly assemble nanostructures at the mesoscale, i.e. ordering nanometer sized particles along micron-sized domains. The missing link is putting together micron-sized arrays into millimeter or centimeter sized shapes, and we believe this can be accomplished by 3D printing technologies. In this project, the students will develop inks made up of nanostructured materials so that they can be printed into three dimensional objects that can be as large as a human hand and demonstrate the capacity to organize matter at the nano-, meso- and macro-scales.

Research area: Nanoscience
Mentor: Igor Slowing

Growth and characterization of novel intermetallic compounds

The SULI student will learn the fundamentals of single crystal growth of new materials, primarily using high temperature solution growth. Depending on the interests of the student and current efforts in the group systems with superconducting, magnetic, structural, and/or electronic transitions will be studied. The SULI student will also become familiar with measurements of thermodynamic (magnetization) and transport (resistivity) properties.

Research area: Condensed Matter Physics
Mentor: Paul Canfield

Nano-plasmonic studies of graphene-based van der Waals systems

Surface plasmon polaritons are collective oscillations of charges on the surface of metals or semiconductors. These surface modes are in vogue for their ability to confine and control electromagnetic waves at length scales much shorter than the diffraction limit. The search for agile plasmonic media is a vibrant research field with promising technological applications. Graphene offers a number of desirable plasmonic characteristics including high confinement, long lifetime, broad spectral range and electrical tunability. These unique properties make graphene a good candidate for plasmonic applications in the technologically-important infrared regime that is not accessible by conventional plasmonics based on noble metals. Despite all the above merits, the plasmonic properties and functionalities of single-layer graphene alone are still limited. One convenient way to engineer graphene plasmons is by constructing van der Waals (vdW) coupled systems based on graphene and/or other layered materials. Indeed, the two-dimensional (2D) nature of graphene makes it extremely sensitive to interlayer coupling that could dramatically modify the properties of Dirac fermions and their plasmonic excitations. In this project, the undergraduate student will work with graduate students to explore novel plasmonic properties and functionalities through systematic nano-infrared studies of various types of graphene-based vdW systems. The objectives of this research are (1) to design and fabricate graphene-based vdW systems by accurately controlling the stacking order, (2) to excite, probe, and characterize plasmons in these vdW structures with the advanced near-field nanoscope, (3) to extract essential parameters of the observed plasmons through rigorous modeling of the experimental data, (4) to achieve active control and manipulations of these plasmons by electrical gating and optical pumping.

Research area: Condensed Matter Physics
Mentor: Zhe Fei

Quantum information science-- modeling the control of qubits

Quantum information science (QIS) is one of the fastest evolving fields of science and technology, and holds enormous potential for quantum computing, communication and information storage. QIS has promise for solving computational problems that can not be presently accomplished. While the classical bit exists in 2 states 0 and 1, the basic element in QIS is the qubit – represented by a local spin vector. Since the spin vector can point in any direction, potentially far greater information can be stored in a qubit than a classical bit.

A very attractive solid-state qubit that we are studying consists of a rare earth (RE) ion in an insulating host crystal. The RE ion has a spin moment that can be addressed and controlled.

In this project we will model the behavior of these qubits in nanocavities that enhance the intensity of light in the cavity, and enhance the interaction of light with the qubit. We will simulate how the state if the qubit can be changed with external photons.

Research area: Condensed Matter Physics
Mentor: Rana Biswas

Electronic structure of rare earth materials

Rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in technology, environment, and the economy is attracting scientists all over the world to investigate them, beginning with the extraction to physical and chemical properties measurements. Although a lot of work has been done on the experimentation of rare-earths, true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research area: Engineering Materials
Mentor: Durga Paudyal

SULI available research projects

Research Area: Materials Sciences Mentor: Georgiy Akopov

Developing Functionalized Graphene for Biomass Conversion

Research area: Nanoscience

Hybrid nanostructures for catalysis

Investigation of Caloric Refrigeration Concepts

Self assembly and crystallization of nano-particles

Research Area: Materials Sciences Mentor: Long Qi

Research Area: Materials Sciences Mentor: Georgiy Akopov

Our research focuses on using imaging methods to discover and to exploit nanoscale heterogeneity in various systems. Laser-based detection systems and sophisticated data analysis are employed in the process. Our work is highly collaborative and involves other DOE-funded researchers.

Research Area: Analytical Chemistry Mentor: Jacob Petrich

Research Area: Materials Sciences
Mentor: Georgiy Akopov

Research Area: Materials Sciences
Mentor: Long Qi

Research Area: Materials Sciences
Mentor: Georgiy Akopov

Research Area: Analytical Chemistry
Mentor: Jacob Petrich